1670 lines
167 KiB
HTML
1670 lines
167 KiB
HTML
<!DOCTYPE html>
|
|
<html lang="en">
|
|
<head>
|
|
<meta charset="UTF-8">
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
|
<title>PozzettiAndrea/ComfyUI-SAM3 - Test Results</title>
|
|
<style>
|
|
* { margin: 0; padding: 0; box-sizing: border-box; }
|
|
|
|
body {
|
|
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
|
|
background: #0f1923;
|
|
color: #e6edf3;
|
|
min-height: 100vh;
|
|
line-height: 1.6;
|
|
}
|
|
|
|
header {
|
|
background: #162033;
|
|
padding: 1.25rem 2rem;
|
|
border-bottom: 1px solid #243656;
|
|
}
|
|
|
|
body.in-iframe header {
|
|
display: none;
|
|
}
|
|
|
|
body.in-iframe .container {
|
|
padding-top: 1.25rem;
|
|
}
|
|
|
|
body.in-iframe .summary-meta {
|
|
display: flex;
|
|
gap: 0.5rem;
|
|
flex-wrap: wrap;
|
|
margin-bottom: 1rem;
|
|
}
|
|
|
|
h1 {
|
|
font-size: 1.25rem;
|
|
font-weight: 600;
|
|
margin-bottom: 0.5rem;
|
|
}
|
|
|
|
h1 a {
|
|
color: #e6edf3;
|
|
text-decoration: none;
|
|
}
|
|
|
|
h1 a:hover { color: #58a6ff; }
|
|
|
|
.meta-chips {
|
|
display: flex;
|
|
gap: 0.5rem;
|
|
flex-wrap: wrap;
|
|
align-items: center;
|
|
}
|
|
|
|
.meta-chip {
|
|
display: inline-flex;
|
|
align-items: center;
|
|
gap: 0.35rem;
|
|
padding: 0.2rem 0.6rem;
|
|
background: #1c2d44;
|
|
border: 1px solid #243656;
|
|
border-radius: 2rem;
|
|
font-size: 0.75rem;
|
|
color: #8ba3c1;
|
|
}
|
|
|
|
.meta-chip svg {
|
|
width: 12px;
|
|
height: 12px;
|
|
fill: currentColor;
|
|
flex-shrink: 0;
|
|
}
|
|
|
|
.container {
|
|
max-width: 1400px;
|
|
margin: 0 auto;
|
|
padding: 2rem;
|
|
}
|
|
|
|
/* Summary Section */
|
|
.summary {
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
padding: 1.5rem;
|
|
margin-bottom: 2rem;
|
|
}
|
|
|
|
.progress-wrapper {
|
|
display: flex;
|
|
align-items: center;
|
|
gap: 1rem;
|
|
margin-bottom: 1rem;
|
|
}
|
|
|
|
.progress-bar {
|
|
background: #1c2d44;
|
|
border-radius: 6px;
|
|
height: 10px;
|
|
overflow: hidden;
|
|
flex: 1;
|
|
}
|
|
|
|
.progress-fill {
|
|
background: #3fb950;
|
|
height: 100%;
|
|
border-radius: 6px;
|
|
transition: width 0.3s ease;
|
|
}
|
|
|
|
.progress-fill.has-failures {
|
|
background: linear-gradient(90deg, #3fb950 0%, #3fb950 0.0%, #f85149 0.0%, #f85149 100%);
|
|
width: 100% !important;
|
|
border-radius: 6px;
|
|
}
|
|
|
|
.progress-label {
|
|
font-size: 0.85rem;
|
|
font-weight: 600;
|
|
color: #8ba3c1;
|
|
white-space: nowrap;
|
|
min-width: 3.5rem;
|
|
text-align: right;
|
|
}
|
|
|
|
.stats {
|
|
display: flex;
|
|
gap: 0.75rem;
|
|
flex-wrap: wrap;
|
|
align-items: center;
|
|
}
|
|
|
|
.stat-badge {
|
|
padding: 0.35rem 0.75rem;
|
|
border-radius: 2rem;
|
|
font-weight: 600;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
.stat-pass {
|
|
background: rgba(63, 185, 80, 0.15);
|
|
color: #3fb950;
|
|
}
|
|
|
|
.stat-fail {
|
|
background: rgba(248, 81, 73, 0.15);
|
|
color: #f85149;
|
|
}
|
|
|
|
.stat-total {
|
|
color: #8ba3c1;
|
|
font-size: 0.85rem;
|
|
}
|
|
|
|
/* Failed Section */
|
|
.failed-section {
|
|
background: rgba(248, 81, 73, 0.08);
|
|
border: 1px solid rgba(248, 81, 73, 0.3);
|
|
border-radius: 8px;
|
|
padding: 1.25rem;
|
|
margin-bottom: 2rem;
|
|
}
|
|
|
|
.failed-section h2 {
|
|
color: #f85149;
|
|
font-size: 0.9rem;
|
|
font-weight: 600;
|
|
margin-bottom: 0.75rem;
|
|
}
|
|
|
|
.failed-item {
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 6px;
|
|
padding: 1rem;
|
|
margin-bottom: 0.5rem;
|
|
}
|
|
|
|
.failed-item:last-child {
|
|
margin-bottom: 0;
|
|
}
|
|
|
|
.failed-header {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
margin-bottom: 0.5rem;
|
|
}
|
|
|
|
.failed-name {
|
|
font-weight: 600;
|
|
color: #f85149;
|
|
}
|
|
|
|
.failed-duration {
|
|
color: #8ba3c1;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
.failed-error {
|
|
background: #0f1923;
|
|
border: 1px solid #243656;
|
|
padding: 0.75rem;
|
|
border-radius: 6px;
|
|
font-family: 'SFMono-Regular', 'Menlo', 'Monaco', monospace;
|
|
font-size: 0.8rem;
|
|
color: #d29922;
|
|
margin-bottom: 0.5rem;
|
|
}
|
|
|
|
.log-link {
|
|
color: #58a6ff;
|
|
text-decoration: none;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
.log-link:hover {
|
|
text-decoration: underline;
|
|
}
|
|
|
|
/* Workflow Grid */
|
|
.section-header {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
margin-bottom: 1.25rem;
|
|
}
|
|
|
|
.section-title {
|
|
font-size: 0.8rem;
|
|
color: #8ba3c1;
|
|
font-weight: 600;
|
|
text-transform: uppercase;
|
|
letter-spacing: 0.06em;
|
|
}
|
|
|
|
.view-controls {
|
|
display: flex;
|
|
gap: 0;
|
|
align-items: center;
|
|
border: 1px solid #243656;
|
|
border-radius: 6px;
|
|
overflow: hidden;
|
|
}
|
|
|
|
.view-btn {
|
|
background: #1c2d44;
|
|
color: #8ba3c1;
|
|
border: none;
|
|
border-right: 1px solid #243656;
|
|
padding: 0.3rem 0.75rem;
|
|
cursor: pointer;
|
|
font-size: 0.75rem;
|
|
font-weight: 500;
|
|
transition: all 0.15s;
|
|
}
|
|
|
|
.view-btn:last-child {
|
|
border-right: none;
|
|
}
|
|
|
|
.view-btn:hover {
|
|
background: #243656;
|
|
color: #e6edf3;
|
|
}
|
|
|
|
.view-btn.active {
|
|
background: #58a6ff;
|
|
color: #fff;
|
|
}
|
|
|
|
.workflow-grid {
|
|
display: grid;
|
|
grid-template-columns: repeat(4, 1fr);
|
|
gap: 1rem;
|
|
}
|
|
|
|
.workflow-grid.view-list {
|
|
grid-template-columns: 1fr;
|
|
gap: 0;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-card {
|
|
border-radius: 0;
|
|
border-bottom: 1px solid #243656;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-card:first-child {
|
|
border-radius: 8px 8px 0 0;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-card:last-child {
|
|
border-radius: 0 0 8px 8px;
|
|
border-bottom: none;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-card:only-child {
|
|
border-radius: 8px;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-screenshot {
|
|
width: 100%;
|
|
height: auto;
|
|
aspect-ratio: auto;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-info {
|
|
border-top: 1px solid #243656;
|
|
padding: 0.75rem 1rem;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-name {
|
|
max-width: none;
|
|
font-size: 0.9rem;
|
|
}
|
|
|
|
.workflow-card {
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
overflow: hidden;
|
|
transition: transform 0.15s, border-color 0.15s;
|
|
}
|
|
|
|
.workflow-card:hover {
|
|
transform: translateY(-1px);
|
|
border-color: #4a6282;
|
|
}
|
|
|
|
.workflow-card.clickable {
|
|
cursor: pointer;
|
|
}
|
|
|
|
.workflow-card.failed {
|
|
border-color: #f85149;
|
|
}
|
|
|
|
.workflow-card.failed:hover {
|
|
border-color: #f85149;
|
|
}
|
|
|
|
.workflow-screenshot {
|
|
width: 100%;
|
|
aspect-ratio: 16/10;
|
|
object-fit: cover;
|
|
background: #0f1923;
|
|
display: block;
|
|
}
|
|
|
|
.workflow-screenshot.placeholder {
|
|
display: flex;
|
|
align-items: center;
|
|
justify-content: center;
|
|
color: #4a6282;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
.workflow-info {
|
|
padding: 0.75rem 1rem;
|
|
border-top: 1px solid #243656;
|
|
}
|
|
|
|
.workflow-header {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
gap: 0.5rem;
|
|
margin-bottom: 0.25rem;
|
|
}
|
|
|
|
.workflow-name {
|
|
font-weight: 500;
|
|
font-size: 0.85rem;
|
|
color: #e6edf3;
|
|
white-space: nowrap;
|
|
overflow: hidden;
|
|
text-overflow: ellipsis;
|
|
max-width: 65%;
|
|
}
|
|
|
|
.workflow-badge {
|
|
padding: 0.15rem 0.5rem;
|
|
border-radius: 2rem;
|
|
font-size: 0.7rem;
|
|
font-weight: 600;
|
|
text-transform: uppercase;
|
|
letter-spacing: 0.03em;
|
|
flex-shrink: 0;
|
|
}
|
|
|
|
.workflow-badge.pass {
|
|
background: rgba(63, 185, 80, 0.15);
|
|
color: #3fb950;
|
|
}
|
|
|
|
.workflow-badge.fail {
|
|
background: rgba(248, 81, 73, 0.15);
|
|
color: #f85149;
|
|
}
|
|
|
|
.workflow-meta {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
font-size: 0.75rem;
|
|
color: #4a6282;
|
|
}
|
|
|
|
/* Lightbox */
|
|
.lightbox {
|
|
display: none;
|
|
position: fixed;
|
|
top: 0;
|
|
left: 0;
|
|
width: 100%;
|
|
height: 100%;
|
|
background: rgba(1, 4, 9, 0.9);
|
|
z-index: 1000;
|
|
justify-content: center;
|
|
align-items: flex-start;
|
|
padding: 2rem;
|
|
overflow-y: auto;
|
|
}
|
|
|
|
.lightbox.active {
|
|
display: flex;
|
|
}
|
|
|
|
.lightbox-content {
|
|
display: flex;
|
|
flex-direction: column;
|
|
max-width: 1200px;
|
|
width: 100%;
|
|
margin: auto;
|
|
}
|
|
|
|
.lightbox-content img {
|
|
max-width: 100%;
|
|
max-height: 60vh;
|
|
object-fit: contain;
|
|
border-radius: 8px;
|
|
border: 1px solid #243656;
|
|
align-self: center;
|
|
cursor: zoom-in;
|
|
}
|
|
|
|
.img-overlay {
|
|
display: none;
|
|
position: fixed;
|
|
top: 0;
|
|
left: 0;
|
|
width: 100vw;
|
|
height: 100vh;
|
|
z-index: 1002;
|
|
background: rgba(1, 4, 9, 0.95);
|
|
overflow: auto;
|
|
align-items: center;
|
|
justify-content: center;
|
|
}
|
|
|
|
.img-overlay.active {
|
|
display: flex;
|
|
}
|
|
|
|
.img-overlay.zoomed {
|
|
align-items: flex-start;
|
|
justify-content: flex-start;
|
|
}
|
|
|
|
.img-overlay img {
|
|
max-width: 100%;
|
|
max-height: 100%;
|
|
object-fit: contain;
|
|
cursor: zoom-in;
|
|
}
|
|
|
|
.img-overlay.zoomed img {
|
|
max-width: none;
|
|
max-height: none;
|
|
cursor: zoom-out;
|
|
}
|
|
|
|
.lightbox-close {
|
|
position: fixed;
|
|
top: 1rem;
|
|
right: 1.5rem;
|
|
font-size: 2rem;
|
|
color: #e6edf3;
|
|
cursor: pointer;
|
|
opacity: 0.6;
|
|
background: none;
|
|
border: none;
|
|
z-index: 1001;
|
|
}
|
|
|
|
.lightbox-close:hover {
|
|
opacity: 1;
|
|
}
|
|
|
|
.lightbox-nav {
|
|
position: fixed;
|
|
top: 50%;
|
|
transform: translateY(-50%);
|
|
background: rgba(22, 32, 51, 0.8);
|
|
border: 1px solid #243656;
|
|
color: #e6edf3;
|
|
font-size: 2.5rem;
|
|
width: 48px;
|
|
height: 64px;
|
|
border-radius: 8px;
|
|
cursor: pointer;
|
|
opacity: 0.6;
|
|
z-index: 1001;
|
|
display: flex;
|
|
align-items: center;
|
|
justify-content: center;
|
|
transition: opacity 0.15s;
|
|
padding: 0;
|
|
line-height: 1;
|
|
}
|
|
|
|
.lightbox-nav:hover {
|
|
opacity: 1;
|
|
}
|
|
|
|
.lightbox-nav-left { left: 1rem; }
|
|
.lightbox-nav-right { right: 1rem; }
|
|
|
|
.lightbox-info {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
padding: 1rem 1.25rem;
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
margin-top: 1rem;
|
|
}
|
|
|
|
.lightbox-title {
|
|
font-size: 1rem;
|
|
font-weight: 600;
|
|
color: #e6edf3;
|
|
}
|
|
|
|
.lightbox-hardware {
|
|
display: block;
|
|
font-size: 0.75rem;
|
|
color: #8ba3c1;
|
|
margin-top: 0.25rem;
|
|
}
|
|
|
|
.lightbox-meta {
|
|
display: flex;
|
|
gap: 1rem;
|
|
align-items: center;
|
|
}
|
|
|
|
.lightbox-badge {
|
|
padding: 0.25rem 0.75rem;
|
|
border-radius: 2rem;
|
|
font-size: 0.8rem;
|
|
font-weight: 600;
|
|
text-transform: uppercase;
|
|
}
|
|
|
|
.lightbox-badge.pass {
|
|
background: rgba(63, 185, 80, 0.15);
|
|
color: #3fb950;
|
|
}
|
|
|
|
.lightbox-badge.fail {
|
|
background: rgba(248, 81, 73, 0.15);
|
|
color: #f85149;
|
|
}
|
|
|
|
.lightbox-duration {
|
|
color: #8ba3c1;
|
|
font-size: 0.85rem;
|
|
}
|
|
|
|
.lightbox-log {
|
|
background: #0f1923;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
padding: 1rem;
|
|
margin-top: 1rem;
|
|
max-height: 300px;
|
|
overflow-y: auto;
|
|
font-family: 'SFMono-Regular', 'Menlo', 'Monaco', monospace;
|
|
font-size: 0.8rem;
|
|
line-height: 1.5;
|
|
white-space: pre-wrap;
|
|
word-break: break-all;
|
|
color: #8ba3c1;
|
|
}
|
|
|
|
.lightbox-log::-webkit-scrollbar {
|
|
width: 8px;
|
|
}
|
|
|
|
.lightbox-log::-webkit-scrollbar-track {
|
|
background: #162033;
|
|
border-radius: 4px;
|
|
}
|
|
|
|
.lightbox-log::-webkit-scrollbar-thumb {
|
|
background: #243656;
|
|
border-radius: 4px;
|
|
}
|
|
|
|
.lightbox-log::-webkit-scrollbar-thumb:hover {
|
|
background: #4a6282;
|
|
}
|
|
|
|
/* Resource Graph */
|
|
.resource-graph {
|
|
display: none;
|
|
margin-top: 1rem;
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
padding: 1rem;
|
|
}
|
|
|
|
.resource-graph.active {
|
|
display: block;
|
|
}
|
|
|
|
.resource-graph-title {
|
|
font-size: 0.8rem;
|
|
color: #8ba3c1;
|
|
font-weight: 500;
|
|
margin-bottom: 0.5rem;
|
|
}
|
|
|
|
.resource-graph canvas {
|
|
width: 100%;
|
|
height: 120px;
|
|
cursor: crosshair;
|
|
}
|
|
|
|
.resource-legend {
|
|
display: flex;
|
|
gap: 1rem;
|
|
margin-top: 0.5rem;
|
|
font-size: 0.75rem;
|
|
color: #8ba3c1;
|
|
}
|
|
|
|
.resource-legend span {
|
|
display: flex;
|
|
align-items: center;
|
|
gap: 4px;
|
|
}
|
|
|
|
.resource-legend .dot {
|
|
width: 8px;
|
|
height: 8px;
|
|
border-radius: 50%;
|
|
}
|
|
|
|
.resource-legend .ram { background: #3fb950; }
|
|
.resource-legend .gpu { background: #d29922; }
|
|
|
|
/* Video Player */
|
|
.video-player {
|
|
display: none;
|
|
margin-top: 1rem;
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
padding: 1rem;
|
|
}
|
|
|
|
.video-player.active {
|
|
display: block;
|
|
}
|
|
|
|
.video-controls {
|
|
display: flex;
|
|
align-items: center;
|
|
gap: 1rem;
|
|
margin-top: 0.5rem;
|
|
}
|
|
|
|
.video-play-btn {
|
|
background: #58a6ff;
|
|
color: #fff;
|
|
border: none;
|
|
padding: 0.4rem 1rem;
|
|
border-radius: 6px;
|
|
cursor: pointer;
|
|
font-size: 0.8rem;
|
|
font-weight: 500;
|
|
}
|
|
|
|
.video-play-btn:hover {
|
|
background: #79b8ff;
|
|
}
|
|
|
|
.video-frame-counter {
|
|
color: #8ba3c1;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
.video-slider-container {
|
|
padding: 15px 0;
|
|
}
|
|
|
|
/* noUiSlider customization */
|
|
#video-slider {
|
|
height: 6px;
|
|
background: #1c2d44;
|
|
border: none;
|
|
box-shadow: none;
|
|
}
|
|
|
|
#video-slider .noUi-connect {
|
|
background: #58a6ff;
|
|
}
|
|
|
|
#video-slider .noUi-handle {
|
|
width: 16px;
|
|
height: 16px;
|
|
background: #58a6ff;
|
|
border: none;
|
|
border-radius: 50%;
|
|
box-shadow: none;
|
|
top: -5px;
|
|
right: -8px;
|
|
cursor: pointer;
|
|
}
|
|
|
|
#video-slider .noUi-handle:before,
|
|
#video-slider .noUi-handle:after {
|
|
display: none;
|
|
}
|
|
|
|
/* Pips (tick marks) */
|
|
.noUi-pips {
|
|
color: #4a6282;
|
|
}
|
|
|
|
.noUi-marker {
|
|
background: #243656;
|
|
width: 2px;
|
|
}
|
|
|
|
.noUi-marker-large {
|
|
height: 12px;
|
|
}
|
|
|
|
.noUi-value {
|
|
display: none;
|
|
}
|
|
|
|
/* Models Section */
|
|
.models-section {
|
|
margin-top: 2rem;
|
|
margin-bottom: 2rem;
|
|
}
|
|
|
|
.models-total {
|
|
font-size: 0.8rem;
|
|
color: #8ba3c1;
|
|
}
|
|
|
|
.models-folder {
|
|
background: #162033;
|
|
border: 1px solid #243656;
|
|
border-radius: 8px;
|
|
margin-bottom: 0.5rem;
|
|
overflow: hidden;
|
|
}
|
|
|
|
.models-folder-header {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
padding: 0.75rem 1rem;
|
|
cursor: pointer;
|
|
user-select: none;
|
|
list-style: none;
|
|
}
|
|
|
|
.models-folder-header::-webkit-details-marker {
|
|
display: none;
|
|
}
|
|
|
|
.models-folder-header::before {
|
|
content: '\25B6';
|
|
font-size: 0.6rem;
|
|
color: #4a6282;
|
|
margin-right: 0.5rem;
|
|
transition: transform 0.15s;
|
|
}
|
|
|
|
.models-folder[open] > .models-folder-header::before {
|
|
transform: rotate(90deg);
|
|
}
|
|
|
|
.models-folder-name {
|
|
font-family: 'SFMono-Regular', 'Menlo', 'Monaco', monospace;
|
|
font-size: 0.85rem;
|
|
font-weight: 600;
|
|
color: #58a6ff;
|
|
}
|
|
|
|
.models-folder-meta {
|
|
display: flex;
|
|
align-items: center;
|
|
gap: 0.75rem;
|
|
}
|
|
|
|
.models-folder-size {
|
|
font-size: 0.8rem;
|
|
font-weight: 600;
|
|
color: #8ba3c1;
|
|
}
|
|
|
|
.models-source-link {
|
|
font-size: 0.75rem;
|
|
color: #3fb950;
|
|
text-decoration: none;
|
|
padding: 0.15rem 0.5rem;
|
|
background: rgba(63, 185, 80, 0.1);
|
|
border: 1px solid rgba(63, 185, 80, 0.2);
|
|
border-radius: 2rem;
|
|
}
|
|
|
|
.models-source-link:hover {
|
|
background: rgba(63, 185, 80, 0.2);
|
|
text-decoration: none;
|
|
}
|
|
|
|
.models-file-list {
|
|
border-top: 1px solid #243656;
|
|
padding: 0.25rem 0;
|
|
}
|
|
|
|
.models-file {
|
|
display: flex;
|
|
justify-content: space-between;
|
|
align-items: center;
|
|
padding: 0.35rem 1rem 0.35rem 2rem;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
.models-file:hover {
|
|
background: rgba(88, 166, 255, 0.05);
|
|
}
|
|
|
|
.models-file-path {
|
|
font-family: 'SFMono-Regular', 'Menlo', 'Monaco', monospace;
|
|
color: #8ba3c1;
|
|
word-break: break-all;
|
|
}
|
|
|
|
.models-file-size {
|
|
color: #4a6282;
|
|
white-space: nowrap;
|
|
margin-left: 1rem;
|
|
flex-shrink: 0;
|
|
}
|
|
|
|
/* Footer */
|
|
footer {
|
|
text-align: center;
|
|
padding: 2.5rem;
|
|
color: #4a6282;
|
|
font-size: 0.8rem;
|
|
}
|
|
|
|
footer a {
|
|
color: #58a6ff;
|
|
text-decoration: none;
|
|
}
|
|
|
|
footer a:hover {
|
|
text-decoration: underline;
|
|
}
|
|
|
|
/* Responsive */
|
|
@media (max-width: 600px) {
|
|
.workflow-grid {
|
|
grid-template-columns: 1fr !important;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-card {
|
|
grid-template-columns: 1fr;
|
|
}
|
|
|
|
.workflow-grid.view-list .workflow-screenshot {
|
|
width: 100%;
|
|
height: auto;
|
|
aspect-ratio: 16/10;
|
|
}
|
|
|
|
.stats {
|
|
flex-direction: column;
|
|
align-items: flex-start;
|
|
}
|
|
|
|
.section-header {
|
|
flex-direction: column;
|
|
align-items: flex-start;
|
|
gap: 0.5rem;
|
|
}
|
|
|
|
.container {
|
|
padding: 1rem;
|
|
}
|
|
}
|
|
</style>
|
|
<link href="https://cdn.jsdelivr.net/npm/nouislider@15/dist/nouislider.min.css" rel="stylesheet">
|
|
<script src="https://cdn.jsdelivr.net/npm/nouislider@15/dist/nouislider.min.js"></script>
|
|
</head>
|
|
<body>
|
|
<header>
|
|
<h1><a href="https://github.com/PozzettiAndrea/PozzettiAndrea/ComfyUI-SAM3">PozzettiAndrea/ComfyUI-SAM3</a> Test Results</h1>
|
|
<div class="meta-chips">
|
|
<span class="meta-chip"><svg viewBox="0 0 16 16"><path d="M8 0a8 8 0 110 16A8 8 0 018 0zm.5 4.5a.5.5 0 00-1 0v3.793L5.854 9.854a.5.5 0 10.708.708l1.853-1.854a.5.5 0 00.085-.094V4.5z"/></svg> 2026-05-10 20:12 UTC</span> <span class="meta-chip"><svg viewBox="0 0 16 16"><path d="M2.5 4a.5.5 0 100 1 .5.5 0 000-1zM4 4.5a.5.5 0 01.5-.5h7a.5.5 0 010 1h-7a.5.5 0 01-.5-.5zM2.5 7a.5.5 0 100 1 .5.5 0 000-1zM4 7.5a.5.5 0 01.5-.5h7a.5.5 0 010 1h-7A.5.5 0 014 7.5zM2.5 10a.5.5 0 100 1 .5.5 0 000-1zM4 10.5a.5.5 0 01.5-.5h7a.5.5 0 010 1h-7a.5.5 0 01-.5-.5z"/></svg> Windows-11-10.0.26200-SP0</span> <span class="meta-chip"><svg viewBox="0 0 16 16"><path d="M5 0a.5.5 0 01.5.5V2h1V.5a.5.5 0 011 0V2h1V.5a.5.5 0 011 0V2h.5A2.5 2.5 0 0112.5 4.5H14v1h-1.5v1H14v1h-1.5v1H14v1h-1.5A2.5 2.5 0 0110 12h-.5v1.5a.5.5 0 01-1 0V12h-1v1.5a.5.5 0 01-1 0V12H6v1.5a.5.5 0 01-1 0V12h-.5A2.5 2.5 0 012 9.5H.5v-1H2v-1H.5v-1H2v-1H.5v-1H2A2.5 2.5 0 014.5 2V.5A.5.5 0 015 0zm-.5 4A1.5 1.5 0 003 5.5v4A1.5 1.5 0 004.5 11h6a1.5 1.5 0 001.5-1.5v-4A1.5 1.5 0 0010.5 4h-6z"/></svg> Intel64 Family 6 Model 79 Stepping 1, GenuineIntel</span>
|
|
</div>
|
|
</header>
|
|
|
|
<div class="container">
|
|
<div class="summary">
|
|
<div class="progress-wrapper">
|
|
<div class="progress-bar">
|
|
<div class="progress-fill has-failures" style="width: 0.0%"></div>
|
|
</div>
|
|
<span class="progress-label">0.0%</span>
|
|
</div>
|
|
<div class="stats">
|
|
<span class="stat-badge stat-pass">0 passed</span>
|
|
<span class="stat-badge stat-fail">5 failed</span>
|
|
<span class="stat-total">0/5 tests</span>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="section-header">
|
|
<h2 class="section-title">Workflows</h2>
|
|
<div class="view-controls">
|
|
<button class="view-btn active" onclick="setView('grid')">Grid</button>
|
|
<button class="view-btn" onclick="setView('list')">List</button>
|
|
</div>
|
|
</div>
|
|
<div class="workflow-grid" id="workflow-grid">
|
|
|
|
<div class="workflow-card clickable failed" onclick="openLightboxByName('image_seg_point')">
|
|
<div class="workflow-screenshot placeholder">No screenshot</div>
|
|
<div class="workflow-info">
|
|
<div class="workflow-header">
|
|
<span class="workflow-name" title="image_seg_point">image_seg_point</span>
|
|
<span class="workflow-badge fail">fail</span>
|
|
</div>
|
|
<div class="workflow-meta">
|
|
<span>37.79s</span>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div class="workflow-card clickable failed" onclick="openLightboxByName('image_seg_text')">
|
|
<div class="workflow-screenshot placeholder">No screenshot</div>
|
|
<div class="workflow-info">
|
|
<div class="workflow-header">
|
|
<span class="workflow-name" title="image_seg_text">image_seg_text</span>
|
|
<span class="workflow-badge fail">fail</span>
|
|
</div>
|
|
<div class="workflow-meta">
|
|
<span>5.83s</span>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div class="workflow-card clickable failed" onclick="openLightboxByName('scene_seg')">
|
|
<div class="workflow-screenshot placeholder">No screenshot</div>
|
|
<div class="workflow-info">
|
|
<div class="workflow-header">
|
|
<span class="workflow-name" title="scene_seg">scene_seg</span>
|
|
<span class="workflow-badge fail">fail</span>
|
|
</div>
|
|
<div class="workflow-meta">
|
|
<span>8.12s</span>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div class="workflow-card clickable failed" onclick="openLightboxByName('scene_seg_interactive')">
|
|
<div class="workflow-screenshot placeholder">No screenshot</div>
|
|
<div class="workflow-info">
|
|
<div class="workflow-header">
|
|
<span class="workflow-name" title="scene_seg_interactive">scene_seg_interactive</span>
|
|
<span class="workflow-badge fail">fail</span>
|
|
</div>
|
|
<div class="workflow-meta">
|
|
<span>6.61s</span>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div class="workflow-card clickable failed" onclick="openLightboxByName('video_point_prompt')">
|
|
<div class="workflow-screenshot placeholder">No screenshot</div>
|
|
<div class="workflow-info">
|
|
<div class="workflow-header">
|
|
<span class="workflow-name" title="video_point_prompt">video_point_prompt</span>
|
|
<span class="workflow-badge fail">fail</span>
|
|
</div>
|
|
<div class="workflow-meta">
|
|
<span>8.95s</span>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
</div>
|
|
|
|
|
|
<div class="failed-section">
|
|
<h2>Failed Tests</h2>
|
|
|
|
<div class="failed-item">
|
|
<div class="failed-header">
|
|
<span class="failed-name">image_seg_point</span>
|
|
<span class="failed-duration">37.79s</span>
|
|
</div>
|
|
<div class="failed-error">Workflow execution failed: {'prompt_id': '86023375-1e85-4626-b82c-f22228be60f2', 'node_id': '31', 'node_type': 'SAM3Segmentation', 'executed': ['1', '30', '15'], 'exception_message': "No module named 'timm'\n", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 297, in process_inputs\n result = f(**inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py", line 149, in wrapped_func\n return method(locked_class, **inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\segmentation.py", line 469, in execute\n sam3_model = get_or_build_model(sam3_model_config)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py", line 32, in get_or_build_model\n from .sam3.predictor import Sam3VideoPredictor\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py", line 61, in <module>\n from .model import (\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py", line 60, in <module>\n from timm.models.layers import DropPath, trunc_normal_\n'], 'current_inputs': {'refinement_iterations': [0], 'use_multimask': [True], 'output_best_mask': [True], 'sam3_model_config': ["{'checkpoint_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\models\\\\sam3\\\\sam3.safetensors', 'bpe_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}"], 'image': ['tensor([[[[0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n ...,\n [0.3176, 0.5765, 0.7176],\n [0.3333, 0.5961, 0.7451],\n [0.3529, 0.6157, 0.7647]],\n\n [[0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n ...,\n [0.3137, 0.5725, 0.7137],\n [0.3137, 0.5765, 0.7255],\n [0.3255, 0.5882, 0.7373]],\n\n [[0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n ...,\n [0.3882, 0.5294, 0.6235],\n [0.3922, 0.5216, 0.6196],\n [0.3961, 0.5255, 0.6235]],\n\n ...,\n\n [[0.4941, 0.4784, 0.4157],\n [0.4941, 0.4784, 0.4157],\n [0.4980, 0.4824, 0.4196],\n ...,\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020]],\n\n [[0.5098, 0.4941, 0.4314],\n [0.5098, 0.4941, 0.4314],\n [0.5137, 0.4980, 0.4353],\n ...,\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020]],\n\n [[0.5176, 0.5020, 0.4392],\n [0.5216, 0.5059, 0.4431],\n [0.5255, 0.5098, 0.4471],\n ...,\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020]]]])'], 'positive_points': ["{'points': [[0.3330291853098248, 0.4464251623052616], [0.32588862185381995, 0.5657519162372204], [0.3373135233834277, 0.7637835504221735]], 'labels': [1, 1, 1]}"], 'negative_points': ["{'points': [], 'labels': []}"]}, 'current_outputs': ['31', '1', '29', '30', '15', '28'], 'timestamp': 1778443891860}
|
|
|
|
Details:
|
|
Workflow: C:\ComfyUI-SAM3\workflows\image_seg_point.json
|
|
Node error: SAM3Segmentation</div>
|
|
</div>
|
|
|
|
<div class="failed-item">
|
|
<div class="failed-header">
|
|
<span class="failed-name">image_seg_text</span>
|
|
<span class="failed-duration">5.83s</span>
|
|
</div>
|
|
<div class="failed-error">Workflow execution failed: {'prompt_id': '260bc77d-fe5b-4b81-97e6-1a0685f84c2c', 'node_id': '15', 'node_type': 'SAM3Grounding', 'executed': ['12', '1'], 'exception_message': "No module named 'timm'\n", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 297, in process_inputs\n result = f(**inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py", line 149, in wrapped_func\n return method(locked_class, **inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\segmentation.py", line 86, in execute\n sam3_model = get_or_build_model(sam3_model_config)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py", line 32, in get_or_build_model\n from .sam3.predictor import Sam3VideoPredictor\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py", line 61, in <module>\n from .model import (\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py", line 60, in <module>\n from timm.models.layers import DropPath, trunc_normal_\n'], 'current_inputs': {'confidence_threshold': [0.2], 'text_prompt': ['child'], 'max_detections': [-1], 'sam3_model_config': ["{'checkpoint_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\models\\\\sam3\\\\sam3.safetensors', 'bpe_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'fp32', 'dtype': 'fp32', 'compile': False}"], 'image': ['tensor([[[[0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n ...,\n [0.3176, 0.5765, 0.7176],\n [0.3333, 0.5961, 0.7451],\n [0.3529, 0.6157, 0.7647]],\n\n [[0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n ...,\n [0.3137, 0.5725, 0.7137],\n [0.3137, 0.5765, 0.7255],\n [0.3255, 0.5882, 0.7373]],\n\n [[0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n [0.2863, 0.4588, 0.5922],\n ...,\n [0.3882, 0.5294, 0.6235],\n [0.3922, 0.5216, 0.6196],\n [0.3961, 0.5255, 0.6235]],\n\n ...,\n\n [[0.4941, 0.4784, 0.4157],\n [0.4941, 0.4784, 0.4157],\n [0.4980, 0.4824, 0.4196],\n ...,\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020]],\n\n [[0.5098, 0.4941, 0.4314],\n [0.5098, 0.4941, 0.4314],\n [0.5137, 0.4980, 0.4353],\n ...,\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020]],\n\n [[0.5176, 0.5020, 0.4392],\n [0.5216, 0.5059, 0.4431],\n [0.5255, 0.5098, 0.4471],\n ...,\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020],\n [0.5608, 0.5529, 0.5020]]]])']}, 'current_outputs': ['12', '1', '4', '15', '3'], 'timestamp': 1778443898050}
|
|
|
|
Details:
|
|
Workflow: C:\ComfyUI-SAM3\workflows\image_seg_text.json
|
|
Node error: SAM3Grounding</div>
|
|
</div>
|
|
|
|
<div class="failed-item">
|
|
<div class="failed-header">
|
|
<span class="failed-name">scene_seg</span>
|
|
<span class="failed-duration">8.12s</span>
|
|
</div>
|
|
<div class="failed-error">Workflow execution failed: {'prompt_id': '71c3363c-b69c-4635-a6d2-719308767ae1', 'node_id': '27', 'node_type': 'SAM3MultipromptSegmentation', 'executed': ['12', '1', '20'], 'exception_message': "No module named 'timm'\n", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 297, in process_inputs\n result = f(**inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py", line 149, in wrapped_func\n return method(locked_class, **inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\segmentation.py", line 695, in execute\n sam3_model = get_or_build_model(sam3_model_config)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py", line 32, in get_or_build_model\n from .sam3.predictor import Sam3VideoPredictor\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py", line 61, in <module>\n from .model import (\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py", line 60, in <module>\n from timm.models.layers import DropPath, trunc_normal_\n'], 'current_inputs': {'refinement_iterations': [0], 'use_multimask': [False], 'sam3_model_config': ["{'checkpoint_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\models\\\\sam3\\\\sam3.safetensors', 'bpe_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'fp32', 'dtype': 'fp32', 'compile': False}"], 'image': ['tensor([[[[0.9176, 0.8392, 0.7333],\n [0.9294, 0.8471, 0.7412],\n [0.9176, 0.8353, 0.7294],\n ...,\n [0.8078, 0.6627, 0.4902],\n [0.8039, 0.6588, 0.4863],\n [0.8157, 0.6706, 0.4980]],\n\n [[0.9137, 0.8353, 0.7294],\n [0.9216, 0.8392, 0.7333],\n [0.9176, 0.8353, 0.7294],\n ...,\n [0.8039, 0.6588, 0.4863],\n [0.8039, 0.6588, 0.4863],\n [0.8118, 0.6667, 0.4941]],\n\n [[0.9137, 0.8314, 0.7255],\n [0.9137, 0.8314, 0.7255],\n [0.9176, 0.8353, 0.7294],\n ...,\n [0.8078, 0.6627, 0.4902],\n [0.8118, 0.6667, 0.4941],\n [0.8039, 0.6588, 0.4863]],\n\n ...,\n\n [[0.8667, 0.6784, 0.4902],\n [0.8706, 0.6824, 0.4941],\n [0.8706, 0.6824, 0.4941],\n ...,\n [0.6471, 0.4431, 0.2549],\n [0.6392, 0.4353, 0.2471],\n [0.6471, 0.4431, 0.2549]],\n\n [[0.8588, 0.6706, 0.4824],\n [0.8667, 0.6784, 0.4902],\n [0.8706, 0.6824, 0.4941],\n ...,\n [0.6431, 0.4392, 0.2510],\n [0.6471, 0.4431, 0.2549],\n [0.6549, 0.4510, 0.2627]],\n\n [[0.8627, 0.6745, 0.4863],\n [0.8667, 0.6784, 0.4902],\n [0.8784, 0.6902, 0.5020],\n ...,\n [0.6353, 0.4314, 0.2431],\n [0.6431, 0.4392, 0.2510],\n [0.6392, 0.4353, 0.2471]]]])'], 'multi_prompts': ["[{'id': 0, 'positive_points': {'points': [[0.7518972528753959, 0.6355044797738758], [0.7340045522905485, 0.6593619024052091], [0.7021953068063758, 0.6623440802341257], [0.6902668397498108, 0.677254969378709], [0.668397983479442, 0.6742727915497924], [0.7180999295484621, 0.6176114128003758], [0.7180999295484621, 0.572878745366626], [0.7439449415043526, 0.5311282557617927], [0.7240641630767446, 0.5609500340509593], [0.6982191511208541, 0.5609500340509593]], 'labels': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.7141237738629407, 0.6056827014847093, 0.15109391604982114, 0.19085938105066613]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 1, 'positive_points': {'points': [[0.6513952517072837, 0.6001522443905642], [0.6354008929467748, 0.6921217188777309], [0.6433980723270292, 0.8680633222444846], [0.8859791801947458, 0.884058013459644], [0.9046392654153393, 0.6041509171943541], [0.9046392654153393, 0.5441708251375063], [0.8060073863922018, 0.5201787883147672]], 'labels': [1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [[0.7180384132094035, 0.5921548987829846], [0.7180384132094035, 0.5921548987829846], [0.7393642248900819, 0.6601323364474121], [0.7393642248900819, 0.6601323364474121], [0.7446956778102515, 0.6841243732701512], [0.7446956778102515, 0.6841243732701512], [0.670055336927877, 0.6721283548587816], [0.670055336927877, 0.6721283548587816], [0.6913811486085556, 0.608149589998144], [0.6913811486085556, 0.608149589998144], [0.6887154221484707, 0.552168170745086], [0.6887154221484707, 0.552168170745086], [0.7100412338291491, 0.552168170745086], [0.7100412338291491, 0.552168170745086], [0.7366984984299972, 0.552168170745086], [0.7366984984299972, 0.552168170745086]], 'labels': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'positive_boxes': {'boxes': [[0.7713529424110994, 0.7141144192985751, 0.31455572229000606, 0.4198606443979348]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 2, 'positive_points': {'points': [[0.5279788816577594, 0.8586378093779201], [0.5097671062510242, 0.6517998210195123], [0.4733435554375539, 0.64789721746558], [0.37968299620291596, 0.64789721746558], [0.39529308940868896, 0.8313195845003946], [0.5565973858683432, 0.8586378093779201], [0.569605796873154, 0.6439946139116478]], 'labels': [1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [[0.4863519664423647, 0.7415597027599534], [0.4863519664423647, 0.7415597027599534], [0.4837502842414026, 0.8508326022700556], [0.4837502842414026, 0.8508326022700556], [0.4473267334279323, 0.8664430164857846], [0.4473267334279323, 0.8664430164857846], [0.43431832242312146, 0.628384199695919], [0.43431832242312146, 0.628384199695919], [0.5123687884519864, 0.5893581641565967], [0.5123687884519864, 0.5893581641565967], [0.5019620596481378, 0.6361894068037834], [0.5019620596481378, 0.6361894068037834], [0.4291149580211971, 0.6400920103577157], [0.4291149580211971, 0.6400920103577157]], 'labels': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'positive_boxes': {'boxes': [[0.47724607873899716, 0.7591214187526485, 0.21593962267985972, 0.24586402389773]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 3, 'positive_points': {'points': [[0.43642532993691785, 0.595717523200948]], 'labels': [1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.4324084720788661, 0.6137937552745099, 0.06426972572882772, 0.07230492829424773]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 4, 'positive_points': {'points': [[0.5006950556657457, 0.595717523200948]], 'labels': [1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.5027034845947715, 0.5716158804361987, 0.09238773073518991, 0.1687114993532448]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 5, 'positive_points': {'points': [[0.9264819886192297, 0.384828149009392], [0.7939256793035224, 0.37880273831820466], [0.7939256793035224, 0.11368466790596292], [0.9304988464772813, 0.10765925721477561], [0.874262836464557, 0.22214206034733455], [0.8501616893162467, 0.22214206034733455], [0.846144831458195, 0.31854863140633155], [0.8983639836128675, 0.3004723993327696], [0.8943471257548158, 0.20406582827377262], [0.8943471257548158, 0.12573548928833755], [0.8421279736001431, 0.1558625427442741], [0.830077400025988, 0.28842157795039497], [0.8220436843098845, 0.33059945278870617]], 'labels': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.8662291207484536, 0.25829452449445844, 0.18477546147037982, 0.31332135594174026]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 6, 'positive_points': {'points': [[0.7045792285036274, 0.9568116711293354], [0.6789425589101554, 0.9568116711293354], [0.6569682706871793, 0.9348369322210276], [0.6716177961691634, 0.9293432474939506], [0.6569682706871793, 0.9403306169481045], [0.7082416098741234, 0.9403306169481045]], 'labels': [1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.6789425589101554, 0.943077459311643, 0.10254667837388842, 0.07141790145200044]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}]"]}, 'current_outputs': ['12', '26', '1', '24', '20', '23', '4', '22', '3', '27'], 'timestamp': 1778443905617}
|
|
|
|
Details:
|
|
Workflow: C:\ComfyUI-SAM3\workflows\scene_seg.json
|
|
Node error: SAM3MultipromptSegmentation</div>
|
|
</div>
|
|
|
|
<div class="failed-item">
|
|
<div class="failed-header">
|
|
<span class="failed-name">scene_seg_interactive</span>
|
|
<span class="failed-duration">6.61s</span>
|
|
</div>
|
|
<div class="failed-error">Workflow execution failed: {'prompt_id': 'a9a9115b-eec6-4d35-b9e2-fcef958a13da', 'node_id': '26', 'node_type': 'SAM3InteractiveCollector', 'executed': ['12', '1'], 'exception_message': "No module named 'timm'\n", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 297, in process_inputs\n result = f(**inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py", line 149, in wrapped_func\n return method(locked_class, **inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3_interactive.py", line 667, in execute\n sam3_model = get_or_build_model(sam3_model_config)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py", line 32, in get_or_build_model\n from .sam3.predictor import Sam3VideoPredictor\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py", line 61, in <module>\n from .model import (\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py", line 60, in <module>\n from timm.models.layers import DropPath, trunc_normal_\n'], 'current_inputs': {'multi_prompts_store': ['[{"positive_points":[{"x":3348.288109906738,"y":2452.2208696844737}],"negative_points":[],"positive_boxes":[],"negative_boxes":[],"name":"Prompt 1"},{"positive_points":[],"negative_points":[],"positive_boxes":[],"negative_boxes":[],"name":"Prompt 2"}]'], 'sam3_model_config': ["{'checkpoint_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\models\\\\sam3\\\\sam3.safetensors', 'bpe_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}"], 'image': ['tensor([[[[0.9176, 0.8392, 0.7333],\n [0.9294, 0.8471, 0.7412],\n [0.9176, 0.8353, 0.7294],\n ...,\n [0.8078, 0.6627, 0.4902],\n [0.8039, 0.6588, 0.4863],\n [0.8157, 0.6706, 0.4980]],\n\n [[0.9137, 0.8353, 0.7294],\n [0.9216, 0.8392, 0.7333],\n [0.9176, 0.8353, 0.7294],\n ...,\n [0.8039, 0.6588, 0.4863],\n [0.8039, 0.6588, 0.4863],\n [0.8118, 0.6667, 0.4941]],\n\n [[0.9137, 0.8314, 0.7255],\n [0.9137, 0.8314, 0.7255],\n [0.9176, 0.8353, 0.7294],\n ...,\n [0.8078, 0.6627, 0.4902],\n [0.8118, 0.6667, 0.4941],\n [0.8039, 0.6588, 0.4863]],\n\n ...,\n\n [[0.8667, 0.6784, 0.4902],\n [0.8706, 0.6824, 0.4941],\n [0.8706, 0.6824, 0.4941],\n ...,\n [0.6471, 0.4431, 0.2549],\n [0.6392, 0.4353, 0.2471],\n [0.6471, 0.4431, 0.2549]],\n\n [[0.8588, 0.6706, 0.4824],\n [0.8667, 0.6784, 0.4902],\n [0.8706, 0.6824, 0.4941],\n ...,\n [0.6431, 0.4392, 0.2510],\n [0.6471, 0.4431, 0.2549],\n [0.6549, 0.4510, 0.2627]],\n\n [[0.8627, 0.6745, 0.4863],\n [0.8667, 0.6784, 0.4902],\n [0.8784, 0.6902, 0.5020],\n ...,\n [0.6353, 0.4314, 0.2431],\n [0.6431, 0.4392, 0.2510],\n [0.6392, 0.4353, 0.2471]]]])']}, 'current_outputs': ['12', '1', '4', '26'], 'timestamp': 1778443913511}
|
|
|
|
Details:
|
|
Workflow: C:\ComfyUI-SAM3\workflows\scene_seg_interactive.json
|
|
Node error: SAM3InteractiveCollector</div>
|
|
</div>
|
|
|
|
<div class="failed-item">
|
|
<div class="failed-header">
|
|
<span class="failed-name">video_point_prompt</span>
|
|
<span class="failed-duration">8.95s</span>
|
|
</div>
|
|
<div class="failed-error">Workflow execution failed: {'prompt_id': 'ec0bb9dd-bd2e-4be1-8ded-e5af63b3b21f', 'node_id': '35', 'node_type': 'SAM3Propagate', 'executed': ['30', '9', '28', '27'], 'exception_message': "No module named 'timm'\n", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 535, in execute\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 335, in get_output_data\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 309, in _async_map_node_over_list\n await process_inputs(input_dict, i)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py", line 297, in process_inputs\n result = f(**inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py", line 149, in wrapped_func\n return method(locked_class, **inputs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py", line 1833, in EXECUTE_NORMALIZED\n to_return = cls.execute(*args, **kwargs)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3_video_nodes.py", line 422, in execute\n sam3_model = get_or_build_model(sam3_model_config)\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py", line 32, in get_or_build_model\n from .sam3.predictor import Sam3VideoPredictor\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py", line 61, in <module>\n from .model import (\n', ' File "C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py", line 60, in <module>\n from timm.models.layers import DropPath, trunc_normal_\n'], 'current_inputs': {'start_frame': [0], 'end_frame': [-1], 'direction': ['forward'], 'sam3_model_config': ["{'checkpoint_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\models\\\\sam3\\\\sam3.safetensors', 'bpe_path': 'C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}"], 'video_state': ["{'session_uuid': 'b380dbbd-30f3-4502-a96d-bd69ddbf2826', 'temp_dir': 'C:\\\\Users\\\\ContainerAdministrator\\\\AppData\\\\Local\\\\Temp\\\\sam3_b380dbbd_b4vrzunp', 'num_frames': 30, 'height': 544, 'width': 960, 'config': {'score_threshold_detection': 0.3, 'new_det_thresh': 0.4, 'fill_hole_area': 16, 'assoc_iou_thresh': 0.1, 'det_nms_thresh': 0.1, 'hotstart_unmatch_thresh': 8, 'hotstart_dup_thresh': 8, 'init_trk_keep_alive': 30, 'hotstart_delay': 15, 'decrease_keep_alive_empty': False, 'suppress_unmatched_globally': False}, 'prompts': [{'frame_idx': 0, 'prompt_type': 'point', 'obj_id': 1, 'data': (((0.38107258850429115, 0.15094459502434338), (0.405779333510521, 0.3307995326922488), (0.43048607851675086, 0.09644309876134173)), (1, 1, 1))}]}"]}, 'current_outputs': ['13', '25', '35', '24', '9', '14', '30', '15', '21', '28', '27'], 'timestamp': 1778443922415}
|
|
|
|
Details:
|
|
Workflow: C:\ComfyUI-SAM3\workflows\video_point_prompt.json
|
|
Node error: SAM3Propagate</div>
|
|
</div>
|
|
|
|
</div>
|
|
|
|
|
|
|
|
<div class="models-section">
|
|
<div class="section-header">
|
|
<h2 class="section-title">Downloaded Models</h2>
|
|
<span class="models-total">1 files · 3.2 GB</span>
|
|
</div>
|
|
|
|
<details class="models-folder" open>
|
|
<summary class="models-folder-header">
|
|
<span class="models-folder-name">models/sam3/</span>
|
|
<span class="models-folder-meta">
|
|
|
|
<span class="models-folder-size">3.2 GB</span>
|
|
</span>
|
|
</summary>
|
|
<div class="models-file-list">
|
|
<div class="models-file"><span class="models-file-path">sam3.safetensors</span><span class="models-file-size">3.2 GB</span></div>
|
|
</div>
|
|
</details>
|
|
|
|
</div>
|
|
|
|
</div>
|
|
|
|
<div class="lightbox" id="lightbox">
|
|
<button class="lightbox-close" onclick="closeLightbox()">×</button>
|
|
<button class="lightbox-nav lightbox-nav-left" onclick="navigateLightbox(-1)">‹</button>
|
|
<button class="lightbox-nav lightbox-nav-right" onclick="navigateLightbox(1)">›</button>
|
|
<div class="lightbox-content">
|
|
<img id="lightbox-img" src="" alt="">
|
|
<video id="lightbox-video" controls preload="metadata" style="display:none; max-width:90vw; max-height:80vh; background:#000;"></video>
|
|
<div class="video-player" id="video-player">
|
|
<div class="video-slider-container">
|
|
<div id="video-slider"></div>
|
|
</div>
|
|
<div class="video-controls">
|
|
<span class="video-frame-counter" id="video-frame-counter">0.0s / 0.0s</span>
|
|
</div>
|
|
</div>
|
|
<div class="resource-graph" id="resource-graph">
|
|
<div class="resource-graph-title">Resource Usage</div>
|
|
<canvas id="resource-canvas"></canvas>
|
|
<div class="resource-legend">
|
|
<span><span class="dot ram"></span> RAM (GB)</span>
|
|
<span id="gpu-legend" style="display:none"><span class="dot gpu"></span> VRAM (GB)</span>
|
|
</div>
|
|
</div>
|
|
<div class="lightbox-info">
|
|
<div>
|
|
<span class="lightbox-title" id="lightbox-title"></span>
|
|
<span class="lightbox-hardware" id="lightbox-hardware"></span>
|
|
</div>
|
|
<div class="lightbox-meta">
|
|
<span class="lightbox-badge" id="lightbox-badge"></span>
|
|
<span class="lightbox-duration" id="lightbox-duration"></span>
|
|
</div>
|
|
</div>
|
|
<pre class="lightbox-log" id="lightbox-log"></pre>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="img-overlay" id="img-overlay">
|
|
<img id="img-overlay-content" src="" alt="">
|
|
</div>
|
|
|
|
<footer>
|
|
Generated by <a href="https://github.com/PozzettiAndrea/comfy-test">comfy-test</a>
|
|
</footer>
|
|
|
|
<script>
|
|
function setView(mode) {
|
|
const grid = document.getElementById('workflow-grid');
|
|
grid.className = mode === 'list' ? 'workflow-grid view-list' : 'workflow-grid';
|
|
document.querySelectorAll('.view-controls .view-btn').forEach(btn => {
|
|
btn.classList.toggle('active', btn.textContent.trim().toLowerCase() === mode);
|
|
});
|
|
}
|
|
|
|
const workflowData = {"image_seg_point": {"src": "", "title": "image_seg_point", "status": "fail", "duration": "37.79", "log": "Capturing execution frames: image_seg_point.json\n [ComfyUI] [DEPRECATION WARNING] Detected import of deprecated legacy API: /extensions/core/widgetInputs.js. This is likely caused by a custom node extension using outdated APIs. Please update your extensions or contact the extension author for an updated version.\n Frame 1 saved (frame_000.jpg, t=0.0s)\n Validating workflow...\n [ComfyUI] === /validate endpoint called ===\n [ComfyUI] Received JSON with keys: ['prompt']\n [ComfyUI] Prompt has 6 nodes\n [ComfyUI] Node 1: LoadImage\n Queuing workflow for execution...\n [ComfyUI] Inputs: {\"image\": \"example_image.jpg\"}\n [ComfyUI] Node 15: SAM3PointCollector\n [ComfyUI] Inputs: {\"points_store\": \"{\\\"positive\\\":[{\\\"x\\\":426.27735719657574,\\\"y\\\":321.42611685978835},{\\\"x\\\":417.13743597288953,\\\"y\\\":407.3413796907987},{\\\"x\\\":431.76130993078743,\\\"y\\\":549.9241563039649}],\\\"negative\\\"\n [ComfyUI] Node 28: PreviewImage\n [ComfyUI] Inputs: {\"images\": [\"31\", 2]}\n [ComfyUI] Node 29: MaskPreview\n [ComfyUI] Inputs: {\"mask\": [\"31\", 0]}\n [ComfyUI] Node 30: LoadSAM3Model\n [ComfyUI] Inputs: {\"precision\": \"auto\", \"compile\": false}\n [ComfyUI] Node 31: SAM3Segmentation\n [ComfyUI] Inputs: {\"refinement_iterations\": 0, \"use_multimask\": true, \"output_best_mask\": true, \"sam3_model_config\": [\"30\", 0], \"image\": [\"1\", 0], \"positive_points\": [\"15\", 0], \"negative_points\": [\"15\", 1]}\n [ComfyUI] Generated prompt_id: fb007d5b-bb10-462c-8ef1-9d4c55538e8a\n [ComfyUI] Calling execution.validate_prompt()...\n [ComfyUI] Validation result: valid=True\n [ComfyUI] === Validation PASSED ===\n [ComfyUI] got prompt\n [ComfyUI] WARNING: 'NoneType' object has no attribute 'shape'\n [ComfyUI] CACHE MISS - computing new result for key=d9204c29\n [ComfyUI] Collected 3 positive, 0 negative points\n [ComfyUI] Image dimensions: 1280x720\n [ComfyUI] Positive point: (426.3, 321.4) -> (0.333, 0.446)\n [ComfyUI] Positive point: (417.1, 407.3) -> (0.326, 0.566)\n [ComfyUI] Positive point: (431.8, 549.9) -> (0.337, 0.764)\n [ComfyUI] Output: 3 positive, 0 negative\n [ComfyUI] [SAM3] Model not found at C:\\workspaces\\SAM3-2207\\ComfyUI\\models\\sam3\\sam3.safetensors, downloading from HuggingFace...\n [ComfyUI] [SAM3] Downloading sam3.safetensors from apozz/sam3-safetensors...\n Node executed (1 total), capturing...\n Frame 2 saved (frame_001.jpg, t=0.6s)\n [capture-node] freeze=5ms shot=150ms unfreeze=6ms saved=True\n Frame 3 saved (frame_002.jpg, t=2.9s)\n [capture-periodic] freeze=4ms shot=138ms unfreeze=5ms saved=True\n [ComfyUI] [SAM3] Download progress: 10%\n Frame 4 saved (frame_003.jpg, t=5.2s)\n [capture-periodic] freeze=8ms shot=141ms unfreeze=10ms saved=True\n [ComfyUI] [SAM3] Download progress: 20%\n [capture-loop] iter=50 t=6.7s state={'complete': False, 'error': None, 'executedCount': 1, 'wsState': 1} eval_ms=5 ram=7.6/31.9GB (24%) swap=0.2/11.4GB (2%) cpu=5% browser_rss=0.72GB\n Frame 5 saved (frame_004.jpg, t=7.4s)\n [capture-periodic] freeze=4ms shot=144ms unfreeze=5ms saved=True\n [ComfyUI] [SAM3] Download progress: 30%\n Frame 6 saved (frame_005.jpg, t=9.7s)\n [capture-periodic] freeze=7ms shot=137ms unfreeze=5ms saved=True\n Frame 7 saved (frame_006.jpg, t=12.0s)\n [capture-periodic] freeze=9ms shot=151ms unfreeze=5ms saved=True\n [ComfyUI] [SAM3] Download progress: 40%\n [capture-loop] iter=100 t=13.6s state={'complete': False, 'error': None, 'executedCount': 1, 'wsState': 1} eval_ms=4 ram=8.2/31.9GB (26%) swap=0.2/11.4GB (2%) cpu=7% browser_rss=0.74GB\n Frame 8 saved (frame_007.jpg, t=14.2s)\n [capture-periodic] freeze=4ms shot=150ms unfreeze=5ms saved=True\n [ComfyUI] [SAM3] Download progress: 50%\n Frame 9 saved (frame_008.jpg, t=16.5s)\n [capture-periodic] freeze=4ms shot=153ms unfreeze=5ms saved=True\n [ComfyUI] [SAM3] Download progress: 60%\n Frame 10 saved (frame_009.jpg, t=18.8s)\n [capture-periodic] freeze=7ms shot=139ms unfreeze=5ms saved=True\n [capture-loop] iter=150 t=19.9s state={'complete': False, 'error': None, 'executedCount': 1, 'wsState': 1} eval_ms=4 ram=8.5/31.9GB (26%) swap=0.2/11.4GB (2%) cpu=10% browser_rss=0.76GB\n Frame 11 saved (frame_010.jpg, t=21.0s)\n [capture-periodic] freeze=5ms shot=151ms unfreeze=7ms saved=True\n [ComfyUI] [SAM3] Download progress: 70%\n Frame 12 saved (frame_011.jpg, t=23.3s)\n [capture-periodic] freeze=4ms shot=166ms unfreeze=5ms saved=True\n [ComfyUI] [SAM3] Download progress: 80%\n Frame 13 saved (frame_012.jpg, t=25.6s)\n [capture-periodic] freeze=4ms shot=140ms unfreeze=5ms saved=True\n [capture-loop] iter=200 t=26.2s state={'complete': False, 'error': None, 'executedCount': 1, 'wsState': 1} eval_ms=8 ram=8.5/31.9GB (27%) swap=0.2/11.4GB (2%) cpu=10% browser_rss=0.76GB\n [ComfyUI] [SAM3] Download progress: 90%\n Frame 14 saved (frame_013.jpg, t=27.8s)\n [capture-periodic] freeze=4ms shot=161ms unfreeze=5ms saved=True\n Frame 15 saved (frame_014.jpg, t=30.1s)\n [capture-periodic] freeze=4ms shot=143ms unfreeze=4ms saved=True\n [ComfyUI] [SAM3] Download progress: 100%\n [ComfyUI] [SAM3] Downloaded sam3.safetensors\n [ComfyUI] [SAM3] Model downloaded successfully\n [ComfyUI] Resolved precision: auto -> bf16\n [ComfyUI] SAM3 model cache miss \ufffd building model...\n [ComfyUI] !!! Exception during processing !!! No module named 'timm'\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 58, in <module>\n [ComfyUI] from timm.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] During handling of the above exception, another exception occurred:\n [ComfyUI] \n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 535, in execute\n [ComfyUI] output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 335, in get_output_data\n [ComfyUI] return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 309, in _async_map_node_over_list\n [ComfyUI] await process_inputs(input_dict, i)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 297, in process_inputs\n [ComfyUI] result = f(**inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py\", line 149, in wrapped_func\n [ComfyUI] return method(locked_class, **inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py\", line 1833, in EXECUTE_NORMALIZED\n [ComfyUI] to_return = cls.execute(*args, **kwargs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\segmentation.py\", line 469, in execute\n [ComfyUI] sam3_model = get_or_build_model(sam3_model_config)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py\", line 32, in get_or_build_model\n [ComfyUI] from .sam3.predictor import Sam3VideoPredictor\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py\", line 61, in <module>\n [ComfyUI] from .model import (\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 60, in <module>\n [ComfyUI] from timm.models.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] Prompt executed in 30.28 seconds\n Execution complete (t=30.6s)\n Execution error: {'prompt_id': '86023375-1e85-4626-b82c-f22228be60f2', 'node_id': '31', 'node_type': 'SAM3Segmentation', 'executed': ['1', '30', '15'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\segmentation.py\", line 469, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'refinement_iterations': [0], 'use_multimask': [True], 'output_best_mask': [True], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}\"], 'image': ['tensor([[[[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3176, 0.5765, 0.7176],\\n [0.3333, 0.5961, 0.7451],\\n [0.3529, 0.6157, 0.7647]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3137, 0.5725, 0.7137],\\n [0.3137, 0.5765, 0.7255],\\n [0.3255, 0.5882, 0.7373]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3882, 0.5294, 0.6235],\\n [0.3922, 0.5216, 0.6196],\\n [0.3961, 0.5255, 0.6235]],\\n\\n ...,\\n\\n [[0.4941, 0.4784, 0.4157],\\n [0.4941, 0.4784, 0.4157],\\n [0.4980, 0.4824, 0.4196],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5098, 0.4941, 0.4314],\\n [0.5098, 0.4941, 0.4314],\\n [0.5137, 0.4980, 0.4353],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5176, 0.5020, 0.4392],\\n [0.5216, 0.5059, 0.4431],\\n [0.5255, 0.5098, 0.4471],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]]]])'], 'positive_points': [\"{'points': [[0.3330291853098248, 0.4464251623052616], [0.32588862185381995, 0.5657519162372204], [0.3373135233834277, 0.7637835504221735]], 'labels': [1, 1, 1]}\"], 'negative_points': [\"{'points': [], 'labels': []}\"]}, 'current_outputs': ['31', '1', '29', '30', '15', '28'], 'timestamp': 1778443891860}\n Status: FAILED\n Error: Workflow execution failed: {'prompt_id': '86023375-1e85-4626-b82c-f22228be60f2', 'node_id': '31', 'node_type': 'SAM3Segmentation', 'executed': ['1', '30', '15'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\segmentation.py\", line 469, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'refinement_iterations': [0], 'use_multimask': [True], 'output_best_mask': [True], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}\"], 'image': ['tensor([[[[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3176, 0.5765, 0.7176],\\n [0.3333, 0.5961, 0.7451],\\n [0.3529, 0.6157, 0.7647]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3137, 0.5725, 0.7137],\\n [0.3137, 0.5765, 0.7255],\\n [0.3255, 0.5882, 0.7373]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3882, 0.5294, 0.6235],\\n [0.3922, 0.5216, 0.6196],\\n [0.3961, 0.5255, 0.6235]],\\n\\n ...,\\n\\n [[0.4941, 0.4784, 0.4157],\\n [0.4941, 0.4784, 0.4157],\\n [0.4980, 0.4824, 0.4196],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5098, 0.4941, 0.4314],\\n [0.5098, 0.4941, 0.4314],\\n [0.5137, 0.4980, 0.4353],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5176, 0.5020, 0.4392],\\n [0.5216, 0.5059, 0.4431],\\n [0.5255, 0.5098, 0.4471],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]]]])'], 'positive_points': [\"{'points': [[0.3330291853098248, 0.4464251623052616], [0.32588862185381995, 0.5657519162372204], [0.3373135233834277, 0.7637835504221735]], 'labels': [1, 1, 1]}\"], 'negative_points': [\"{'points': [], 'labels': []}\"]}, 'current_outputs': ['31', '1', '29', '30', '15', '28'], 'timestamp': 1778443891860}\n Details: Workflow: C:\\ComfyUI-SAM3\\workflows\\image_seg_point.json\nNode error: SAM3Segmentation", "hardware": {"os": "Windows-11-10.0.26200-SP0", "cpu": "Intel64 Family 6 Model 79 Stepping 1, GenuineIntel"}}, "image_seg_text": {"src": "", "title": "image_seg_text", "status": "fail", "duration": "5.83", "log": "Capturing execution frames: image_seg_text.json\n [ComfyUI] Exception in callback _ProactorBasePipeTransport._call_connection_lost(None)\n [ComfyUI] handle: <Handle _ProactorBasePipeTransport._call_connection_lost(None)>\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\Users\\ContainerAdministrator\\AppData\\Roaming\\uv\\python\\cpython-3.10-windows-x86_64-none\\lib\\asyncio\\events.py\", line 80, in _run\n [ComfyUI] self._context.run(self._callback, *self._args)\n [ComfyUI] File \"C:\\Users\\ContainerAdministrator\\AppData\\Roaming\\uv\\python\\cpython-3.10-windows-x86_64-none\\lib\\asyncio\\proactor_events.py\", line 165, in _call_connection_lost\n [ComfyUI] self._sock.shutdown(socket.SHUT_RDWR)\n [ComfyUI] ConnectionResetError: [WinError 10054] An existing connection was forcibly closed by the remote host\n Frame 1 saved (frame_000.jpg, t=0.0s)\n Validating workflow...\n [ComfyUI] === /validate endpoint called ===\n [ComfyUI] Received JSON with keys: ['prompt']\n [ComfyUI] Prompt has 5 nodes\n Queuing workflow for execution...\n [ComfyUI] Node 1: LoadImage\n [ComfyUI] Inputs: {\"image\": \"example_image.jpg\"}\n [ComfyUI] Node 3: PreviewImage\n [ComfyUI] Inputs: {\"images\": [\"15\", 1]}\n [ComfyUI] Node 4: MaskPreview\n [ComfyUI] Inputs: {\"mask\": [\"15\", 0]}\n [ComfyUI] Node 12: LoadSAM3Model\n [ComfyUI] Inputs: {\"precision\": \"fp32\", \"compile\": false}\n [ComfyUI] Node 15: SAM3Grounding\n [ComfyUI] Inputs: {\"confidence_threshold\": 0.2, \"text_prompt\": \"child\", \"max_detections\": -1, \"sam3_model_config\": [\"12\", 0], \"image\": [\"1\", 0]}\n [ComfyUI] Generated prompt_id: 4b286b0b-0a27-43b7-ab6a-20f281bf78a8\n [ComfyUI] Calling execution.validate_prompt()...\n [ComfyUI] Validation result: valid=True\n [ComfyUI] === Validation PASSED ===\n [ComfyUI] got prompt\n [ComfyUI] Resolved precision: fp32 -> fp32\n [ComfyUI] SAM3 model cache miss \ufffd building model...\n [ComfyUI] !!! Exception during processing !!! No module named 'timm'\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 58, in <module>\n [ComfyUI] from timm.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] During handling of the above exception, another exception occurred:\n [ComfyUI] \n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 535, in execute\n [ComfyUI] output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 335, in get_output_data\n [ComfyUI] return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 309, in _async_map_node_over_list\n [ComfyUI] await process_inputs(input_dict, i)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 297, in process_inputs\n [ComfyUI] result = f(**inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py\", line 149, in wrapped_func\n [ComfyUI] return method(locked_class, **inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py\", line 1833, in EXECUTE_NORMALIZED\n [ComfyUI] to_return = cls.execute(*args, **kwargs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\segmentation.py\", line 86, in execute\n [ComfyUI] sam3_model = get_or_build_model(sam3_model_config)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py\", line 32, in get_or_build_model\n [ComfyUI] from .sam3.predictor import Sam3VideoPredictor\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py\", line 61, in <module>\n [ComfyUI] from .model import (\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 60, in <module>\n [ComfyUI] from timm.models.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] Prompt executed in 0.05 seconds\n Execution complete (t=0.4s)\n Execution error: {'prompt_id': '260bc77d-fe5b-4b81-97e6-1a0685f84c2c', 'node_id': '15', 'node_type': 'SAM3Grounding', 'executed': ['12', '1'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\segmentation.py\", line 86, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'confidence_threshold': [0.2], 'text_prompt': ['child'], 'max_detections': [-1], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'fp32', 'dtype': 'fp32', 'compile': False}\"], 'image': ['tensor([[[[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3176, 0.5765, 0.7176],\\n [0.3333, 0.5961, 0.7451],\\n [0.3529, 0.6157, 0.7647]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3137, 0.5725, 0.7137],\\n [0.3137, 0.5765, 0.7255],\\n [0.3255, 0.5882, 0.7373]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3882, 0.5294, 0.6235],\\n [0.3922, 0.5216, 0.6196],\\n [0.3961, 0.5255, 0.6235]],\\n\\n ...,\\n\\n [[0.4941, 0.4784, 0.4157],\\n [0.4941, 0.4784, 0.4157],\\n [0.4980, 0.4824, 0.4196],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5098, 0.4941, 0.4314],\\n [0.5098, 0.4941, 0.4314],\\n [0.5137, 0.4980, 0.4353],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5176, 0.5020, 0.4392],\\n [0.5216, 0.5059, 0.4431],\\n [0.5255, 0.5098, 0.4471],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]]]])']}, 'current_outputs': ['12', '1', '4', '15', '3'], 'timestamp': 1778443898050}\n Status: FAILED\n Error: Workflow execution failed: {'prompt_id': '260bc77d-fe5b-4b81-97e6-1a0685f84c2c', 'node_id': '15', 'node_type': 'SAM3Grounding', 'executed': ['12', '1'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\segmentation.py\", line 86, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'confidence_threshold': [0.2], 'text_prompt': ['child'], 'max_detections': [-1], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'fp32', 'dtype': 'fp32', 'compile': False}\"], 'image': ['tensor([[[[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3176, 0.5765, 0.7176],\\n [0.3333, 0.5961, 0.7451],\\n [0.3529, 0.6157, 0.7647]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3137, 0.5725, 0.7137],\\n [0.3137, 0.5765, 0.7255],\\n [0.3255, 0.5882, 0.7373]],\\n\\n [[0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n [0.2863, 0.4588, 0.5922],\\n ...,\\n [0.3882, 0.5294, 0.6235],\\n [0.3922, 0.5216, 0.6196],\\n [0.3961, 0.5255, 0.6235]],\\n\\n ...,\\n\\n [[0.4941, 0.4784, 0.4157],\\n [0.4941, 0.4784, 0.4157],\\n [0.4980, 0.4824, 0.4196],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5098, 0.4941, 0.4314],\\n [0.5098, 0.4941, 0.4314],\\n [0.5137, 0.4980, 0.4353],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]],\\n\\n [[0.5176, 0.5020, 0.4392],\\n [0.5216, 0.5059, 0.4431],\\n [0.5255, 0.5098, 0.4471],\\n ...,\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020],\\n [0.5608, 0.5529, 0.5020]]]])']}, 'current_outputs': ['12', '1', '4', '15', '3'], 'timestamp': 1778443898050}\n Details: Workflow: C:\\ComfyUI-SAM3\\workflows\\image_seg_text.json\nNode error: SAM3Grounding", "hardware": {"os": "Windows-11-10.0.26200-SP0", "cpu": "Intel64 Family 6 Model 79 Stepping 1, GenuineIntel"}}, "scene_seg": {"src": "", "title": "scene_seg", "status": "fail", "duration": "8.12", "log": "Capturing execution frames: scene_seg.json\n [ComfyUI] Exception in callback _ProactorBasePipeTransport._call_connection_lost(None)\n [ComfyUI] handle: <Handle _ProactorBasePipeTransport._call_connection_lost(None)>\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\Users\\ContainerAdministrator\\AppData\\Roaming\\uv\\python\\cpython-3.10-windows-x86_64-none\\lib\\asyncio\\events.py\", line 80, in _run\n [ComfyUI] self._context.run(self._callback, *self._args)\n [ComfyUI] File \"C:\\Users\\ContainerAdministrator\\AppData\\Roaming\\uv\\python\\cpython-3.10-windows-x86_64-none\\lib\\asyncio\\proactor_events.py\", line 165, in _call_connection_lost\n [ComfyUI] self._sock.shutdown(socket.SHUT_RDWR)\n [ComfyUI] ConnectionResetError: [WinError 10054] An existing connection was forcibly closed by the remote host\n Frame 1 saved (frame_000.jpg, t=0.0s)\n Validating workflow...\n [ComfyUI] === /validate endpoint called ===\n [ComfyUI] Received JSON with keys: ['prompt']\n [ComfyUI] Prompt has 10 nodes\n Queuing workflow for execution...\n [ComfyUI] Node 1: LoadImage\n [ComfyUI] Inputs: {\"image\": \"image.png\"}\n [ComfyUI] Node 3: PreviewImage\n [ComfyUI] Inputs: {\"images\": [\"27\", 1]}\n [ComfyUI] Node 4: MaskPreview\n [ComfyUI] Inputs: {\"mask\": [\"27\", 0]}\n [ComfyUI] Node 12: LoadSAM3Model\n [ComfyUI] Inputs: {\"precision\": \"fp32\", \"compile\": false}\n [ComfyUI] Node 20: SAM3MultiRegionCollector\n [ComfyUI] Inputs: {\"multi_prompts_store\": \"[{\\\"positive_points\\\":[{\\\"x\\\":5052.74953932266,\\\"y\\\":2847.0600693869637},{\\\"x\\\":4932.510591392486,\\\"y\\\":2953.9413227753366},{\\\"x\\\":4718.752461738845,\\\"y\\\":2967.301479448883},{\n [ComfyUI] Node 22: MultibandFromBatch\n [ComfyUI] Inputs: {\"images\": [\"1\", 0], \"masks\": [\"27\", 0]}\n [ComfyUI] Node 23: MultibandSave\n [ComfyUI] Inputs: {\"file_path\": \"output/multiband\", \"format\": \"npz\", \"multiband\": [\"26\", 0]}\n [ComfyUI] Node 24: MultibandPreview\n [ComfyUI] Inputs: {\"channel_index\": 0, \"multiband\": [\"26\", 0]}\n [ComfyUI] Node 26: MultibandResize\n [ComfyUI] Inputs: {\"upscale_method\": \"nearest-exact\", \"width\": 900, \"height\": 600, \"crop\": \"center\", \"multiband\": [\"22\", 0]}\n [ComfyUI] Node 27: SAM3MultipromptSegmentation\n [ComfyUI] Inputs: {\"refinement_iterations\": 0, \"use_multimask\": false, \"sam3_model_config\": [\"12\", 0], \"image\": [\"1\", 0], \"multi_prompts\": [\"20\", 0]}\n [ComfyUI] Generated prompt_id: f09fac32-da84-434f-b2ca-7ac01b201308\n [ComfyUI] Calling execution.validate_prompt()...\n [ComfyUI] Validation result: valid=True\n [ComfyUI] === Validation PASSED ===\n [ComfyUI] got prompt\n [ComfyUI] WARNING: 'NoneType' object has no attribute 'shape'\n [ComfyUI] CACHE MISS - computing new result for key=35316a77\n [ComfyUI] Image dimensions: 6720x4480\n [ComfyUI] Processing 7 prompt regions\n [ComfyUI] Prompt 0: 10 pos pts, 0 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Prompt 1: 7 pos pts, 16 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Prompt 2: 7 pos pts, 14 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Prompt 3: 1 pos pts, 0 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Prompt 4: 1 pos pts, 0 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Prompt 5: 13 pos pts, 0 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Prompt 6: 6 pos pts, 0 neg pts, 1 pos boxes, 0 neg boxes\n [ComfyUI] Output: 7 non-empty prompts\n [ComfyUI] Resolved precision: fp32 -> fp32\n [ComfyUI] SAM3 model cache miss \ufffd building model...\n [ComfyUI] !!! Exception during processing !!! No module named 'timm'\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 58, in <module>\n [ComfyUI] from timm.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] During handling of the above exception, another exception occurred:\n [ComfyUI] \n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 535, in execute\n [ComfyUI] output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 335, in get_output_data\n [ComfyUI] return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 309, in _async_map_node_over_list\n [ComfyUI] await process_inputs(input_dict, i)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 297, in process_inputs\n [ComfyUI] result = f(**inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py\", line 149, in wrapped_func\n [ComfyUI] return method(locked_class, **inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py\", line 1833, in EXECUTE_NORMALIZED\n [ComfyUI] to_return = cls.execute(*args, **kwargs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\segmentation.py\", line 695, in execute\n [ComfyUI] sam3_model = get_or_build_model(sam3_model_config)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py\", line 32, in get_or_build_model\n [ComfyUI] from .sam3.predictor import Sam3VideoPredictor\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py\", line 61, in <module>\n [ComfyUI] from .model import (\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 60, in <module>\n [ComfyUI] from timm.models.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] Prompt executed in 1.22 seconds\n Node executed (1 total), capturing...\n Frame 2 saved (frame_001.jpg, t=2.1s)\n [capture-node] freeze=61ms shot=322ms unfreeze=0ms saved=True\n Execution complete (t=2.1s)\n Execution error: {'prompt_id': '71c3363c-b69c-4635-a6d2-719308767ae1', 'node_id': '27', 'node_type': 'SAM3MultipromptSegmentation', 'executed': ['12', '1', '20'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\segmentation.py\", line 695, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'refinement_iterations': [0], 'use_multimask': [False], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'fp32', 'dtype': 'fp32', 'compile': False}\"], 'image': ['tensor([[[[0.9176, 0.8392, 0.7333],\\n [0.9294, 0.8471, 0.7412],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8039, 0.6588, 0.4863],\\n [0.8157, 0.6706, 0.4980]],\\n\\n [[0.9137, 0.8353, 0.7294],\\n [0.9216, 0.8392, 0.7333],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8039, 0.6588, 0.4863],\\n [0.8039, 0.6588, 0.4863],\\n [0.8118, 0.6667, 0.4941]],\\n\\n [[0.9137, 0.8314, 0.7255],\\n [0.9137, 0.8314, 0.7255],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8118, 0.6667, 0.4941],\\n [0.8039, 0.6588, 0.4863]],\\n\\n ...,\\n\\n [[0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6471, 0.4431, 0.2549],\\n [0.6392, 0.4353, 0.2471],\\n [0.6471, 0.4431, 0.2549]],\\n\\n [[0.8588, 0.6706, 0.4824],\\n [0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6431, 0.4392, 0.2510],\\n [0.6471, 0.4431, 0.2549],\\n [0.6549, 0.4510, 0.2627]],\\n\\n [[0.8627, 0.6745, 0.4863],\\n [0.8667, 0.6784, 0.4902],\\n [0.8784, 0.6902, 0.5020],\\n ...,\\n [0.6353, 0.4314, 0.2431],\\n [0.6431, 0.4392, 0.2510],\\n [0.6392, 0.4353, 0.2471]]]])'], 'multi_prompts': [\"[{'id': 0, 'positive_points': {'points': [[0.7518972528753959, 0.6355044797738758], [0.7340045522905485, 0.6593619024052091], [0.7021953068063758, 0.6623440802341257], [0.6902668397498108, 0.677254969378709], [0.668397983479442, 0.6742727915497924], [0.7180999295484621, 0.6176114128003758], [0.7180999295484621, 0.572878745366626], [0.7439449415043526, 0.5311282557617927], [0.7240641630767446, 0.5609500340509593], [0.6982191511208541, 0.5609500340509593]], 'labels': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.7141237738629407, 0.6056827014847093, 0.15109391604982114, 0.19085938105066613]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 1, 'positive_points': {'points': [[0.6513952517072837, 0.6001522443905642], [0.6354008929467748, 0.6921217188777309], [0.6433980723270292, 0.8680633222444846], [0.8859791801947458, 0.884058013459644], [0.9046392654153393, 0.6041509171943541], [0.9046392654153393, 0.5441708251375063], [0.8060073863922018, 0.5201787883147672]], 'labels': [1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [[0.7180384132094035, 0.5921548987829846], [0.7180384132094035, 0.5921548987829846], [0.7393642248900819, 0.6601323364474121], [0.7393642248900819, 0.6601323364474121], [0.7446956778102515, 0.6841243732701512], [0.7446956778102515, 0.6841243732701512], [0.670055336927877, 0.6721283548587816], [0.670055336927877, 0.6721283548587816], [0.6913811486085556, 0.608149589998144], [0.6913811486085556, 0.608149589998144], [0.6887154221484707, 0.552168170745086], [0.6887154221484707, 0.552168170745086], [0.7100412338291491, 0.552168170745086], [0.7100412338291491, 0.552168170745086], [0.7366984984299972, 0.552168170745086], [0.7366984984299972, 0.552168170745086]], 'labels': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'positive_boxes': {'boxes': [[0.7713529424110994, 0.7141144192985751, 0.31455572229000606, 0.4198606443979348]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 2, 'positive_points': {'points': [[0.5279788816577594, 0.8586378093779201], [0.5097671062510242, 0.6517998210195123], [0.4733435554375539, 0.64789721746558], [0.37968299620291596, 0.64789721746558], [0.39529308940868896, 0.8313195845003946], [0.5565973858683432, 0.8586378093779201], [0.569605796873154, 0.6439946139116478]], 'labels': [1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [[0.4863519664423647, 0.7415597027599534], [0.4863519664423647, 0.7415597027599534], [0.4837502842414026, 0.8508326022700556], [0.4837502842414026, 0.8508326022700556], [0.4473267334279323, 0.8664430164857846], [0.4473267334279323, 0.8664430164857846], [0.43431832242312146, 0.628384199695919], [0.43431832242312146, 0.628384199695919], [0.5123687884519864, 0.5893581641565967], [0.5123687884519864, 0.5893581641565967], [0.5019620596481378, 0.6361894068037834], [0.5019620596481378, 0.6361894068037834], [0.4291149580211971, 0.6400920103577157], [0.4291149580211971, 0.6400920103577157]], 'labels': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'positive_boxes': {'boxes': [[0.47724607873899716, 0.7591214187526485, 0.21593962267985972, 0.24586402389773]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 3, 'positive_points': {'points': [[0.43642532993691785, 0.595717523200948]], 'labels': [1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.4324084720788661, 0.6137937552745099, 0.06426972572882772, 0.07230492829424773]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 4, 'positive_points': {'points': [[0.5006950556657457, 0.595717523200948]], 'labels': [1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.5027034845947715, 0.5716158804361987, 0.09238773073518991, 0.1687114993532448]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 5, 'positive_points': {'points': [[0.9264819886192297, 0.384828149009392], [0.7939256793035224, 0.37880273831820466], [0.7939256793035224, 0.11368466790596292], [0.9304988464772813, 0.10765925721477561], [0.874262836464557, 0.22214206034733455], [0.8501616893162467, 0.22214206034733455], [0.846144831458195, 0.31854863140633155], [0.8983639836128675, 0.3004723993327696], [0.8943471257548158, 0.20406582827377262], [0.8943471257548158, 0.12573548928833755], [0.8421279736001431, 0.1558625427442741], [0.830077400025988, 0.28842157795039497], [0.8220436843098845, 0.33059945278870617]], 'labels': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.8662291207484536, 0.25829452449445844, 0.18477546147037982, 0.31332135594174026]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 6, 'positive_points': {'points': [[0.7045792285036274, 0.9568116711293354], [0.6789425589101554, 0.9568116711293354], [0.6569682706871793, 0.9348369322210276], [0.6716177961691634, 0.9293432474939506], [0.6569682706871793, 0.9403306169481045], [0.7082416098741234, 0.9403306169481045]], 'labels': [1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.6789425589101554, 0.943077459311643, 0.10254667837388842, 0.07141790145200044]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}]\"]}, 'current_outputs': ['12', '26', '1', '24', '20', '23', '4', '22', '3', '27'], 'timestamp': 1778443905617}\n Status: FAILED\n Error: Workflow execution failed: {'prompt_id': '71c3363c-b69c-4635-a6d2-719308767ae1', 'node_id': '27', 'node_type': 'SAM3MultipromptSegmentation', 'executed': ['12', '1', '20'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\segmentation.py\", line 695, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'refinement_iterations': [0], 'use_multimask': [False], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'fp32', 'dtype': 'fp32', 'compile': False}\"], 'image': ['tensor([[[[0.9176, 0.8392, 0.7333],\\n [0.9294, 0.8471, 0.7412],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8039, 0.6588, 0.4863],\\n [0.8157, 0.6706, 0.4980]],\\n\\n [[0.9137, 0.8353, 0.7294],\\n [0.9216, 0.8392, 0.7333],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8039, 0.6588, 0.4863],\\n [0.8039, 0.6588, 0.4863],\\n [0.8118, 0.6667, 0.4941]],\\n\\n [[0.9137, 0.8314, 0.7255],\\n [0.9137, 0.8314, 0.7255],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8118, 0.6667, 0.4941],\\n [0.8039, 0.6588, 0.4863]],\\n\\n ...,\\n\\n [[0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6471, 0.4431, 0.2549],\\n [0.6392, 0.4353, 0.2471],\\n [0.6471, 0.4431, 0.2549]],\\n\\n [[0.8588, 0.6706, 0.4824],\\n [0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6431, 0.4392, 0.2510],\\n [0.6471, 0.4431, 0.2549],\\n [0.6549, 0.4510, 0.2627]],\\n\\n [[0.8627, 0.6745, 0.4863],\\n [0.8667, 0.6784, 0.4902],\\n [0.8784, 0.6902, 0.5020],\\n ...,\\n [0.6353, 0.4314, 0.2431],\\n [0.6431, 0.4392, 0.2510],\\n [0.6392, 0.4353, 0.2471]]]])'], 'multi_prompts': [\"[{'id': 0, 'positive_points': {'points': [[0.7518972528753959, 0.6355044797738758], [0.7340045522905485, 0.6593619024052091], [0.7021953068063758, 0.6623440802341257], [0.6902668397498108, 0.677254969378709], [0.668397983479442, 0.6742727915497924], [0.7180999295484621, 0.6176114128003758], [0.7180999295484621, 0.572878745366626], [0.7439449415043526, 0.5311282557617927], [0.7240641630767446, 0.5609500340509593], [0.6982191511208541, 0.5609500340509593]], 'labels': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.7141237738629407, 0.6056827014847093, 0.15109391604982114, 0.19085938105066613]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 1, 'positive_points': {'points': [[0.6513952517072837, 0.6001522443905642], [0.6354008929467748, 0.6921217188777309], [0.6433980723270292, 0.8680633222444846], [0.8859791801947458, 0.884058013459644], [0.9046392654153393, 0.6041509171943541], [0.9046392654153393, 0.5441708251375063], [0.8060073863922018, 0.5201787883147672]], 'labels': [1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [[0.7180384132094035, 0.5921548987829846], [0.7180384132094035, 0.5921548987829846], [0.7393642248900819, 0.6601323364474121], [0.7393642248900819, 0.6601323364474121], [0.7446956778102515, 0.6841243732701512], [0.7446956778102515, 0.6841243732701512], [0.670055336927877, 0.6721283548587816], [0.670055336927877, 0.6721283548587816], [0.6913811486085556, 0.608149589998144], [0.6913811486085556, 0.608149589998144], [0.6887154221484707, 0.552168170745086], [0.6887154221484707, 0.552168170745086], [0.7100412338291491, 0.552168170745086], [0.7100412338291491, 0.552168170745086], [0.7366984984299972, 0.552168170745086], [0.7366984984299972, 0.552168170745086]], 'labels': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'positive_boxes': {'boxes': [[0.7713529424110994, 0.7141144192985751, 0.31455572229000606, 0.4198606443979348]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 2, 'positive_points': {'points': [[0.5279788816577594, 0.8586378093779201], [0.5097671062510242, 0.6517998210195123], [0.4733435554375539, 0.64789721746558], [0.37968299620291596, 0.64789721746558], [0.39529308940868896, 0.8313195845003946], [0.5565973858683432, 0.8586378093779201], [0.569605796873154, 0.6439946139116478]], 'labels': [1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [[0.4863519664423647, 0.7415597027599534], [0.4863519664423647, 0.7415597027599534], [0.4837502842414026, 0.8508326022700556], [0.4837502842414026, 0.8508326022700556], [0.4473267334279323, 0.8664430164857846], [0.4473267334279323, 0.8664430164857846], [0.43431832242312146, 0.628384199695919], [0.43431832242312146, 0.628384199695919], [0.5123687884519864, 0.5893581641565967], [0.5123687884519864, 0.5893581641565967], [0.5019620596481378, 0.6361894068037834], [0.5019620596481378, 0.6361894068037834], [0.4291149580211971, 0.6400920103577157], [0.4291149580211971, 0.6400920103577157]], 'labels': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'positive_boxes': {'boxes': [[0.47724607873899716, 0.7591214187526485, 0.21593962267985972, 0.24586402389773]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 3, 'positive_points': {'points': [[0.43642532993691785, 0.595717523200948]], 'labels': [1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.4324084720788661, 0.6137937552745099, 0.06426972572882772, 0.07230492829424773]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 4, 'positive_points': {'points': [[0.5006950556657457, 0.595717523200948]], 'labels': [1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.5027034845947715, 0.5716158804361987, 0.09238773073518991, 0.1687114993532448]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 5, 'positive_points': {'points': [[0.9264819886192297, 0.384828149009392], [0.7939256793035224, 0.37880273831820466], [0.7939256793035224, 0.11368466790596292], [0.9304988464772813, 0.10765925721477561], [0.874262836464557, 0.22214206034733455], [0.8501616893162467, 0.22214206034733455], [0.846144831458195, 0.31854863140633155], [0.8983639836128675, 0.3004723993327696], [0.8943471257548158, 0.20406582827377262], [0.8943471257548158, 0.12573548928833755], [0.8421279736001431, 0.1558625427442741], [0.830077400025988, 0.28842157795039497], [0.8220436843098845, 0.33059945278870617]], 'labels': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.8662291207484536, 0.25829452449445844, 0.18477546147037982, 0.31332135594174026]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}, {'id': 6, 'positive_points': {'points': [[0.7045792285036274, 0.9568116711293354], [0.6789425589101554, 0.9568116711293354], [0.6569682706871793, 0.9348369322210276], [0.6716177961691634, 0.9293432474939506], [0.6569682706871793, 0.9403306169481045], [0.7082416098741234, 0.9403306169481045]], 'labels': [1, 1, 1, 1, 1, 1]}, 'negative_points': {'points': [], 'labels': []}, 'positive_boxes': {'boxes': [[0.6789425589101554, 0.943077459311643, 0.10254667837388842, 0.07141790145200044]], 'labels': [True]}, 'negative_boxes': {'boxes': [], 'labels': []}}]\"]}, 'current_outputs': ['12', '26', '1', '24', '20', '23', '4', '22', '3', '27'], 'timestamp': 1778443905617}\n Details: Workflow: C:\\ComfyUI-SAM3\\workflows\\scene_seg.json\nNode error: SAM3MultipromptSegmentation", "hardware": {"os": "Windows-11-10.0.26200-SP0", "cpu": "Intel64 Family 6 Model 79 Stepping 1, GenuineIntel"}}, "scene_seg_interactive": {"src": "", "title": "scene_seg_interactive", "status": "fail", "duration": "6.61", "log": "Capturing execution frames: scene_seg_interactive.json\n Frame 1 saved (frame_000.jpg, t=0.0s)\n Validating workflow...\n [ComfyUI] === /validate endpoint called ===\n [ComfyUI] Received JSON with keys: ['prompt']\n [ComfyUI] Prompt has 4 nodes\n Queuing workflow for execution...\n [ComfyUI] Node 1: LoadImage\n [ComfyUI] Inputs: {\"image\": \"image.png\"}\n [ComfyUI] Node 4: MaskPreview\n [ComfyUI] Inputs: {\"mask\": [\"26\", 0]}\n [ComfyUI] Node 12: LoadSAM3Model\n [ComfyUI] Inputs: {\"precision\": \"auto\", \"compile\": false}\n [ComfyUI] Node 26: SAM3InteractiveCollector\n [ComfyUI] Inputs: {\"multi_prompts_store\": \"[{\\\"positive_points\\\":[{\\\"x\\\":3348.288109906738,\\\"y\\\":2452.2208696844737}],\\\"negative_points\\\":[],\\\"positive_boxes\\\":[],\\\"negative_boxes\\\":[],\\\"name\\\":\\\"Prompt 1\\\"},{\\\"positiv\n [ComfyUI] Generated prompt_id: b1da449f-6171-4ba2-ab2a-98407280d909\n [ComfyUI] Calling execution.validate_prompt()...\n [ComfyUI] Validation result: valid=True\n [ComfyUI] === Validation PASSED ===\n [ComfyUI] got prompt\n [ComfyUI] WARNING: 'NoneType' object has no attribute 'shape'\n [ComfyUI] Resolved precision: auto -> bf16\n [ComfyUI] SAM3 model cache miss \ufffd building model...\n [ComfyUI] !!! Exception during processing !!! No module named 'timm'\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 58, in <module>\n [ComfyUI] from timm.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] During handling of the above exception, another exception occurred:\n [ComfyUI] \n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 535, in execute\n [ComfyUI] output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 335, in get_output_data\n [ComfyUI] return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 309, in _async_map_node_over_list\n [ComfyUI] await process_inputs(input_dict, i)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 297, in process_inputs\n [ComfyUI] result = f(**inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py\", line 149, in wrapped_func\n [ComfyUI] return method(locked_class, **inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py\", line 1833, in EXECUTE_NORMALIZED\n [ComfyUI] to_return = cls.execute(*args, **kwargs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3_interactive.py\", line 667, in execute\n [ComfyUI] sam3_model = get_or_build_model(sam3_model_config)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py\", line 32, in get_or_build_model\n [ComfyUI] from .sam3.predictor import Sam3VideoPredictor\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py\", line 61, in <module>\n [ComfyUI] from .model import (\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 60, in <module>\n [ComfyUI] from timm.models.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] Prompt executed in 0.76 seconds\n Execution complete (t=1.0s)\n Execution error: {'prompt_id': 'a9a9115b-eec6-4d35-b9e2-fcef958a13da', 'node_id': '26', 'node_type': 'SAM3InteractiveCollector', 'executed': ['12', '1'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3_interactive.py\", line 667, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'multi_prompts_store': ['[{\"positive_points\":[{\"x\":3348.288109906738,\"y\":2452.2208696844737}],\"negative_points\":[],\"positive_boxes\":[],\"negative_boxes\":[],\"name\":\"Prompt 1\"},{\"positive_points\":[],\"negative_points\":[],\"positive_boxes\":[],\"negative_boxes\":[],\"name\":\"Prompt 2\"}]'], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}\"], 'image': ['tensor([[[[0.9176, 0.8392, 0.7333],\\n [0.9294, 0.8471, 0.7412],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8039, 0.6588, 0.4863],\\n [0.8157, 0.6706, 0.4980]],\\n\\n [[0.9137, 0.8353, 0.7294],\\n [0.9216, 0.8392, 0.7333],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8039, 0.6588, 0.4863],\\n [0.8039, 0.6588, 0.4863],\\n [0.8118, 0.6667, 0.4941]],\\n\\n [[0.9137, 0.8314, 0.7255],\\n [0.9137, 0.8314, 0.7255],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8118, 0.6667, 0.4941],\\n [0.8039, 0.6588, 0.4863]],\\n\\n ...,\\n\\n [[0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6471, 0.4431, 0.2549],\\n [0.6392, 0.4353, 0.2471],\\n [0.6471, 0.4431, 0.2549]],\\n\\n [[0.8588, 0.6706, 0.4824],\\n [0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6431, 0.4392, 0.2510],\\n [0.6471, 0.4431, 0.2549],\\n [0.6549, 0.4510, 0.2627]],\\n\\n [[0.8627, 0.6745, 0.4863],\\n [0.8667, 0.6784, 0.4902],\\n [0.8784, 0.6902, 0.5020],\\n ...,\\n [0.6353, 0.4314, 0.2431],\\n [0.6431, 0.4392, 0.2510],\\n [0.6392, 0.4353, 0.2471]]]])']}, 'current_outputs': ['12', '1', '4', '26'], 'timestamp': 1778443913511}\n Status: FAILED\n Error: Workflow execution failed: {'prompt_id': 'a9a9115b-eec6-4d35-b9e2-fcef958a13da', 'node_id': '26', 'node_type': 'SAM3InteractiveCollector', 'executed': ['12', '1'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3_interactive.py\", line 667, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'multi_prompts_store': ['[{\"positive_points\":[{\"x\":3348.288109906738,\"y\":2452.2208696844737}],\"negative_points\":[],\"positive_boxes\":[],\"negative_boxes\":[],\"name\":\"Prompt 1\"},{\"positive_points\":[],\"negative_points\":[],\"positive_boxes\":[],\"negative_boxes\":[],\"name\":\"Prompt 2\"}]'], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}\"], 'image': ['tensor([[[[0.9176, 0.8392, 0.7333],\\n [0.9294, 0.8471, 0.7412],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8039, 0.6588, 0.4863],\\n [0.8157, 0.6706, 0.4980]],\\n\\n [[0.9137, 0.8353, 0.7294],\\n [0.9216, 0.8392, 0.7333],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8039, 0.6588, 0.4863],\\n [0.8039, 0.6588, 0.4863],\\n [0.8118, 0.6667, 0.4941]],\\n\\n [[0.9137, 0.8314, 0.7255],\\n [0.9137, 0.8314, 0.7255],\\n [0.9176, 0.8353, 0.7294],\\n ...,\\n [0.8078, 0.6627, 0.4902],\\n [0.8118, 0.6667, 0.4941],\\n [0.8039, 0.6588, 0.4863]],\\n\\n ...,\\n\\n [[0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6471, 0.4431, 0.2549],\\n [0.6392, 0.4353, 0.2471],\\n [0.6471, 0.4431, 0.2549]],\\n\\n [[0.8588, 0.6706, 0.4824],\\n [0.8667, 0.6784, 0.4902],\\n [0.8706, 0.6824, 0.4941],\\n ...,\\n [0.6431, 0.4392, 0.2510],\\n [0.6471, 0.4431, 0.2549],\\n [0.6549, 0.4510, 0.2627]],\\n\\n [[0.8627, 0.6745, 0.4863],\\n [0.8667, 0.6784, 0.4902],\\n [0.8784, 0.6902, 0.5020],\\n ...,\\n [0.6353, 0.4314, 0.2431],\\n [0.6431, 0.4392, 0.2510],\\n [0.6392, 0.4353, 0.2471]]]])']}, 'current_outputs': ['12', '1', '4', '26'], 'timestamp': 1778443913511}\n Details: Workflow: C:\\ComfyUI-SAM3\\workflows\\scene_seg_interactive.json\nNode error: SAM3InteractiveCollector", "hardware": {"os": "Windows-11-10.0.26200-SP0", "cpu": "Intel64 Family 6 Model 79 Stepping 1, GenuineIntel"}}, "video_point_prompt": {"src": "", "title": "video_point_prompt", "status": "fail", "duration": "8.95", "log": "Capturing execution frames: video_point_prompt.json\n Frame 1 saved (frame_000.jpg, t=0.0s)\n Validating workflow...\n [ComfyUI] === /validate endpoint called ===\n [ComfyUI] Received JSON with keys: ['prompt']\n [ComfyUI] Prompt has 11 nodes\n [ComfyUI] Node 9: VHS_LoadVideo\n Queuing workflow for execution...\n [ComfyUI] Inputs: {\"video\": \"bedroom.mp4\", \"force_rate\": 0, \"custom_width\": 0, \"custom_height\": 0, \"frame_load_cap\": 30, \"skip_first_frames\": 0, \"select_every_nth\": 1, \"format\": \"AnimateDiff\"}\n [ComfyUI] Node 13: CreateVideo\n [ComfyUI] Inputs: {\"fps\": 30, \"images\": [\"14\", 0]}\n [ComfyUI] Node 14: MaskToImage\n [ComfyUI] Inputs: {\"mask\": [\"21\", 0]}\n [ComfyUI] Node 15: SaveVideo\n [ComfyUI] Inputs: {\"filename_prefix\": \"video/ComfyUI\", \"format\": \"auto\", \"codec\": \"auto\", \"video\": [\"13\", 0]}\n [ComfyUI] Node 21: SAM3VideoOutput\n [ComfyUI] Inputs: {\"obj_id\": 0, \"plot_all_masks\": true, \"masks\": [\"35\", 0], \"video_state\": [\"35\", 2], \"scores\": [\"35\", 1]}\n [ComfyUI] Node 24: CreateVideo\n [ComfyUI] Inputs: {\"fps\": 30, \"images\": [\"21\", 2]}\n [ComfyUI] Node 25: SaveVideo\n [ComfyUI] Inputs: {\"filename_prefix\": \"video/ComfyUI\", \"format\": \"auto\", \"codec\": \"auto\", \"video\": [\"24\", 0]}\n [ComfyUI] Node 27: SAM3VideoSegmentation\n [ComfyUI] Inputs: {\"prompt_mode\": \"point\", \"frame_idx\": 0.3, \"score_threshold\": 0.3, \"video_frames\": [\"9\", 0], \"positive_points\": [\"28\", 0]}\n [ComfyUI] Node 28: SAM3PointCollector\n [ComfyUI] Inputs: {\"points_store\": \"{\\\"positive\\\":[{\\\"x\\\":365.8296849641195,\\\"y\\\":82.1138596932428},{\\\"x\\\":389.5481601701001,\\\"y\\\":179.95494578458334},{\\\"x\\\":413.26663537608084,\\\"y\\\":52.465045726169905}],\\\"negative\\\":[\n [ComfyUI] Node 30: LoadSAM3Model\n [ComfyUI] Inputs: {\"precision\": \"auto\", \"compile\": false}\n [ComfyUI] Node 35: SAM3Propagate\n [ComfyUI] Inputs: {\"start_frame\": 0, \"end_frame\": -1, \"direction\": \"forward\", \"sam3_model_config\": [\"30\", 0], \"video_state\": [\"27\", 0]}\n [ComfyUI] Generated prompt_id: c2ecb26c-833c-4f98-816b-44e84ea98ae7\n [ComfyUI] Calling execution.validate_prompt()...\n [ComfyUI] Validation result: valid=True\n [ComfyUI] === Validation PASSED ===\n [ComfyUI] got prompt\n [ComfyUI] fingerprint_inputs SAM3Propagate: session=None\n [ComfyUI] fingerprint_inputs SAM3Propagate: returning (None, None, 0, -1, 'forward')\n [ComfyUI] fingerprint_inputs SAM3VideoSegmentation: video_hash=9356dabdc8862dff08a9ab9d174121c1, prompt_mode=point\n [ComfyUI] fingerprint_inputs SAM3VideoSegmentation: positive_points=None\n [ComfyUI] fingerprint_inputs SAM3VideoSegmentation: negative_points=None\n [ComfyUI] fingerprint_inputs SAM3VideoSegmentation: returning hash=5079830374410607645\n [ComfyUI] WARNING: 'NoneType' object has no attribute 'shape'\n [ComfyUI] CACHE MISS - computing new result for key=d7f60d60\n [ComfyUI] Collected 3 positive, 0 negative points\n [ComfyUI] Image dimensions: 960x544\n [ComfyUI] Positive point: (365.8, 82.1) -> (0.381, 0.151)\n [ComfyUI] Positive point: (389.5, 180.0) -> (0.406, 0.331)\n [ComfyUI] Positive point: (413.3, 52.5) -> (0.430, 0.096)\n [ComfyUI] Output: 3 positive, 0 negative\n [ComfyUI] CACHE MISS - computing new video_state for key=1a64b375\n [ComfyUI] [MEM] Before video segmentation: VRAM 0.00GB alloc / 0.00GB reserved | RAM: 1.09GB (process), 8.1/31.9GB (system)\n [ComfyUI] Saving 30 frames to C:\\Users\\ContainerAdministrator\\AppData\\Local\\Temp\\sam3_b380dbbd_b4vrzunp\n Frame 2 saved (frame_001.jpg, t=2.3s)\n [capture-periodic] freeze=6ms shot=152ms unfreeze=19ms saved=True\n Node executed (1 total), capturing...\n [ComfyUI] Frames saved successfully\n [ComfyUI] Initialized session b380dbbd\n [ComfyUI] Frames: 30, Size: 960x544\n [ComfyUI] Prompt mode: point\n [ComfyUI] Added point prompt: obj=1, positive=3, negative=0\n [ComfyUI] Total prompts: 1\n [ComfyUI] [MEM] After video segmentation: VRAM 0.00GB alloc / 0.00GB reserved | RAM: 1.09GB (process), 8.1/31.9GB (system)\n [ComfyUI] Resolved precision: auto -> bf16\n [ComfyUI] SAM3 model cache miss \ufffd building model...\n [ComfyUI] !!! Exception during processing !!! No module named 'timm'\n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 58, in <module>\n [ComfyUI] from timm.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] During handling of the above exception, another exception occurred:\n [ComfyUI] \n [ComfyUI] Traceback (most recent call last):\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 535, in execute\n [ComfyUI] output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 335, in get_output_data\n [ComfyUI] return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 309, in _async_map_node_over_list\n [ComfyUI] await process_inputs(input_dict, i)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\execution.py\", line 297, in process_inputs\n [ComfyUI] result = f(**inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\internal\\__init__.py\", line 149, in wrapped_func\n [ComfyUI] return method(locked_class, **inputs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\comfy_api\\latest\\_io.py\", line 1833, in EXECUTE_NORMALIZED\n [ComfyUI] to_return = cls.execute(*args, **kwargs)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3_video_nodes.py\", line 422, in execute\n [ComfyUI] sam3_model = get_or_build_model(sam3_model_config)\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\_model_cache.py\", line 32, in get_or_build_model\n [ComfyUI] from .sam3.predictor import Sam3VideoPredictor\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\__init__.py\", line 61, in <module>\n [ComfyUI] from .model import (\n [ComfyUI] File \"C:\\workspaces\\SAM3-2207\\ComfyUI\\custom_nodes\\ComfyUI-SAM3\\nodes\\sam3\\model.py\", line 60, in <module>\n [ComfyUI] from timm.models.layers import DropPath, trunc_normal_\n [ComfyUI] ModuleNotFoundError: No module named 'timm'\n [ComfyUI] \n [ComfyUI] Prompt executed in 2.52 seconds\n Frame 3 saved (frame_002.jpg, t=2.8s)\n [capture-node] freeze=4ms shot=161ms unfreeze=5ms saved=True\n Execution complete (t=3.1s)\n Execution error: {'prompt_id': 'ec0bb9dd-bd2e-4be1-8ded-e5af63b3b21f', 'node_id': '35', 'node_type': 'SAM3Propagate', 'executed': ['30', '9', '28', '27'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3_video_nodes.py\", line 422, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'start_frame': [0], 'end_frame': [-1], 'direction': ['forward'], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}\"], 'video_state': [\"{'session_uuid': 'b380dbbd-30f3-4502-a96d-bd69ddbf2826', 'temp_dir': 'C:\\\\\\\\Users\\\\\\\\ContainerAdministrator\\\\\\\\AppData\\\\\\\\Local\\\\\\\\Temp\\\\\\\\sam3_b380dbbd_b4vrzunp', 'num_frames': 30, 'height': 544, 'width': 960, 'config': {'score_threshold_detection': 0.3, 'new_det_thresh': 0.4, 'fill_hole_area': 16, 'assoc_iou_thresh': 0.1, 'det_nms_thresh': 0.1, 'hotstart_unmatch_thresh': 8, 'hotstart_dup_thresh': 8, 'init_trk_keep_alive': 30, 'hotstart_delay': 15, 'decrease_keep_alive_empty': False, 'suppress_unmatched_globally': False}, 'prompts': [{'frame_idx': 0, 'prompt_type': 'point', 'obj_id': 1, 'data': (((0.38107258850429115, 0.15094459502434338), (0.405779333510521, 0.3307995326922488), (0.43048607851675086, 0.09644309876134173)), (1, 1, 1))}]}\"]}, 'current_outputs': ['13', '25', '35', '24', '9', '14', '30', '15', '21', '28', '27'], 'timestamp': 1778443922415}\n Status: FAILED\n Error: Workflow execution failed: {'prompt_id': 'ec0bb9dd-bd2e-4be1-8ded-e5af63b3b21f', 'node_id': '35', 'node_type': 'SAM3Propagate', 'executed': ['30', '9', '28', '27'], 'exception_message': \"No module named 'timm'\\n\", 'exception_type': 'ModuleNotFoundError', 'traceback': [' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 535, in execute\\n output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 335, in get_output_data\\n return_values = await _async_map_node_over_list(prompt_id, unique_id, obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 309, in _async_map_node_over_list\\n await process_inputs(input_dict, i)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\execution.py\", line 297, in process_inputs\\n result = f(**inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\internal\\\\__init__.py\", line 149, in wrapped_func\\n return method(locked_class, **inputs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\comfy_api\\\\latest\\\\_io.py\", line 1833, in EXECUTE_NORMALIZED\\n to_return = cls.execute(*args, **kwargs)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3_video_nodes.py\", line 422, in execute\\n sam3_model = get_or_build_model(sam3_model_config)\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\_model_cache.py\", line 32, in get_or_build_model\\n from .sam3.predictor import Sam3VideoPredictor\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\__init__.py\", line 61, in <module>\\n from .model import (\\n', ' File \"C:\\\\workspaces\\\\SAM3-2207\\\\ComfyUI\\\\custom_nodes\\\\ComfyUI-SAM3\\\\nodes\\\\sam3\\\\model.py\", line 60, in <module>\\n from timm.models.layers import DropPath, trunc_normal_\\n'], 'current_inputs': {'start_frame': [0], 'end_frame': [-1], 'direction': ['forward'], 'sam3_model_config': [\"{'checkpoint_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\models\\\\\\\\sam3\\\\\\\\sam3.safetensors', 'bpe_path': 'C:\\\\\\\\workspaces\\\\\\\\SAM3-2207\\\\\\\\ComfyUI\\\\\\\\custom_nodes\\\\\\\\ComfyUI-SAM3\\\\\\\\nodes\\\\\\\\sam3\\\\\\\\bpe_simple_vocab_16e6.txt.gz', 'precision': 'auto', 'dtype': 'bf16', 'compile': False}\"], 'video_state': [\"{'session_uuid': 'b380dbbd-30f3-4502-a96d-bd69ddbf2826', 'temp_dir': 'C:\\\\\\\\Users\\\\\\\\ContainerAdministrator\\\\\\\\AppData\\\\\\\\Local\\\\\\\\Temp\\\\\\\\sam3_b380dbbd_b4vrzunp', 'num_frames': 30, 'height': 544, 'width': 960, 'config': {'score_threshold_detection': 0.3, 'new_det_thresh': 0.4, 'fill_hole_area': 16, 'assoc_iou_thresh': 0.1, 'det_nms_thresh': 0.1, 'hotstart_unmatch_thresh': 8, 'hotstart_dup_thresh': 8, 'init_trk_keep_alive': 30, 'hotstart_delay': 15, 'decrease_keep_alive_empty': False, 'suppress_unmatched_globally': False}, 'prompts': [{'frame_idx': 0, 'prompt_type': 'point', 'obj_id': 1, 'data': (((0.38107258850429115, 0.15094459502434338), (0.405779333510521, 0.3307995326922488), (0.43048607851675086, 0.09644309876134173)), (1, 1, 1))}]}\"]}, 'current_outputs': ['13', '25', '35', '24', '9', '14', '30', '15', '21', '28', '27'], 'timestamp': 1778443922415}\n Details: Workflow: C:\\ComfyUI-SAM3\\workflows\\video_point_prompt.json\nNode error: SAM3Propagate", "hardware": {"os": "Windows-11-10.0.26200-SP0", "cpu": "Intel64 Family 6 Model 79 Stepping 1, GenuineIntel"}}};
|
|
const workflowNames = Object.keys(workflowData);
|
|
const videoData = {};
|
|
|
|
const inIframe = window !== window.top;
|
|
let currentWorkflow = null;
|
|
let playInterval = null;
|
|
let originalLogContent = '';
|
|
let currentFrameIndex = 0;
|
|
let currentFrames = [];
|
|
let currentTotalTime = 0;
|
|
|
|
function openLightboxByName(name) {
|
|
const w = workflowData[name];
|
|
if (w) openLightbox(w.src, w.title, w.status, w.duration, w.log, w.hardware);
|
|
}
|
|
|
|
function openLightbox(src, title, status, duration, logContent, hardware) {
|
|
document.getElementById('lightbox-img').src = src;
|
|
document.getElementById('lightbox-title').textContent = title;
|
|
currentWorkflow = title;
|
|
originalLogContent = logContent;
|
|
|
|
const badge = document.getElementById('lightbox-badge');
|
|
badge.textContent = status;
|
|
badge.className = 'lightbox-badge ' + status;
|
|
|
|
document.getElementById('lightbox-duration').textContent = duration + 's';
|
|
document.getElementById('lightbox-log').textContent = logContent || '(No log available)';
|
|
|
|
const hwEl = document.getElementById('lightbox-hardware');
|
|
if (hardware) {
|
|
const parts = [];
|
|
if (hardware.os) parts.push(hardware.os);
|
|
if (hardware.cpu) parts.push(hardware.cpu);
|
|
if (hardware.gpu) parts.push(hardware.gpu);
|
|
hwEl.textContent = parts.join(' | ');
|
|
} else {
|
|
hwEl.textContent = status === 'skipped' ? '(Did not run on this machine)' : '';
|
|
}
|
|
|
|
const data = videoData[title];
|
|
const videoPlayer = document.getElementById('video-player');
|
|
const lightboxImg = document.getElementById('lightbox-img');
|
|
const lightboxVideo = document.getElementById('lightbox-video');
|
|
|
|
// Reset both modes; the branch below activates one.
|
|
videoPlayer.classList.remove('active');
|
|
lightboxVideo.style.display = 'none';
|
|
lightboxVideo.removeAttribute('src');
|
|
lightboxImg.style.display = '';
|
|
|
|
if (data && data.mp4) {
|
|
// Playable mp4 (desktop runs). Show <video>, hide the
|
|
// frame-slideshow img + slider.
|
|
lightboxVideo.src = 'videos/' + encodeURIComponent(title) + '/' + data.mp4;
|
|
lightboxVideo.style.display = '';
|
|
lightboxImg.style.display = 'none';
|
|
} else if (data && data.frames && data.frames.length > 1) {
|
|
currentFrames = data.frames;
|
|
currentTotalTime = data.total_time || data.frames[data.frames.length - 1].time;
|
|
setupVideoSlider(data.frames, currentTotalTime);
|
|
updateVideoFrameByIndex(title, data.frames.length - 1);
|
|
videoPlayer.classList.add('active');
|
|
}
|
|
|
|
loadResourceGraph(title);
|
|
|
|
// Close image overlay if open
|
|
closeImgOverlay();
|
|
|
|
document.getElementById('lightbox').classList.add('active');
|
|
history.replaceState(null, '', '#' + encodeURIComponent(title));
|
|
|
|
// Notify parent frames for deep linking
|
|
if (inIframe) {
|
|
window.parent.postMessage({ type: 'comfytest-open', name: title }, '*');
|
|
}
|
|
}
|
|
|
|
function buildSliderRange(frames, totalTime) {
|
|
const range = { 'min': frames[0].time };
|
|
frames.forEach((frame, idx) => {
|
|
if (idx > 0 && idx < frames.length - 1) {
|
|
const pct = (frame.time / totalTime * 100).toFixed(1) + '%';
|
|
range[pct] = frame.time;
|
|
}
|
|
});
|
|
range['max'] = frames[frames.length - 1].time;
|
|
return range;
|
|
}
|
|
|
|
function setupVideoSlider(frames, totalTime) {
|
|
const sliderEl = document.getElementById('video-slider');
|
|
|
|
if (sliderEl.noUiSlider) {
|
|
sliderEl.noUiSlider.destroy();
|
|
}
|
|
|
|
const range = buildSliderRange(frames, totalTime);
|
|
|
|
noUiSlider.create(sliderEl, {
|
|
start: frames[frames.length - 1].time,
|
|
snap: true,
|
|
range: range,
|
|
pips: {
|
|
mode: 'range',
|
|
density: 100
|
|
}
|
|
});
|
|
|
|
sliderEl.noUiSlider.on('update', function(values) {
|
|
const time = parseFloat(values[0]);
|
|
const frameIdx = frames.findIndex(f => Math.abs(f.time - time) < 0.01);
|
|
if (frameIdx >= 0 && frameIdx !== currentFrameIndex) {
|
|
currentFrameIndex = frameIdx;
|
|
showFrame(currentWorkflow, frameIdx);
|
|
}
|
|
});
|
|
}
|
|
|
|
function showFrame(workflowName, frameIndex) {
|
|
const data = videoData[workflowName];
|
|
if (!data || !data.frames) return;
|
|
|
|
const frame = data.frames[frameIndex];
|
|
const img = document.getElementById('lightbox-img');
|
|
|
|
const isLastFrame = frameIndex === data.frames.length - 1;
|
|
if (isLastFrame && workflowData[workflowName] && workflowData[workflowName].src) {
|
|
img.src = workflowData[workflowName].src;
|
|
} else {
|
|
img.src = 'videos/' + workflowName + '/' + frame.file;
|
|
}
|
|
|
|
const counter = document.getElementById('video-frame-counter');
|
|
const totalTime = data.total_time || data.frames[data.frames.length - 1].time;
|
|
counter.textContent = frame.time.toFixed(1) + 's / ' + totalTime.toFixed(1) + 's';
|
|
|
|
const logEl = document.getElementById('lightbox-log');
|
|
if (frame.log) {
|
|
logEl.textContent = frame.log;
|
|
logEl.scrollTop = logEl.scrollHeight;
|
|
}
|
|
}
|
|
|
|
function updateVideoFrameByIndex(workflowName, frameIndex) {
|
|
currentFrameIndex = frameIndex;
|
|
showFrame(workflowName, frameIndex);
|
|
|
|
const sliderEl = document.getElementById('video-slider');
|
|
if (sliderEl.noUiSlider && currentFrames[frameIndex]) {
|
|
sliderEl.noUiSlider.set(currentFrames[frameIndex].time);
|
|
}
|
|
}
|
|
|
|
function toggleVideoPlay() {
|
|
const btn = document.getElementById('video-play-btn');
|
|
if (playInterval) {
|
|
clearInterval(playInterval);
|
|
playInterval = null;
|
|
btn.innerHTML = '▶ Play';
|
|
} else {
|
|
btn.innerHTML = '■ Stop';
|
|
playInterval = setInterval(() => {
|
|
if (!currentFrames.length) return;
|
|
currentFrameIndex = (currentFrameIndex + 1) % currentFrames.length;
|
|
updateVideoFrameByIndex(currentWorkflow, currentFrameIndex);
|
|
}, 500);
|
|
}
|
|
}
|
|
|
|
let resourceGraphState = null;
|
|
|
|
async function loadResourceGraph(workflowName) {
|
|
const graphContainer = document.getElementById('resource-graph');
|
|
const canvas = document.getElementById('resource-canvas');
|
|
const gpuLegend = document.getElementById('gpu-legend');
|
|
|
|
resourceGraphState = null;
|
|
|
|
try {
|
|
const csvResponse = await fetch('logs/' + workflowName + '_resources.csv');
|
|
|
|
if (!csvResponse.ok) {
|
|
graphContainer.classList.remove('active');
|
|
return;
|
|
}
|
|
|
|
const text = await csvResponse.text();
|
|
const allLines = text.trim().split('\n');
|
|
|
|
let totalRamGb = 32;
|
|
if (allLines[0].startsWith('#')) {
|
|
const metaMatch = allLines[0].match(/total_ram_gb=([\d.]+)/);
|
|
if (metaMatch) {
|
|
totalRamGb = parseFloat(metaMatch[1]);
|
|
}
|
|
}
|
|
|
|
const dataLines = allLines.slice(2);
|
|
|
|
if (dataLines.length < 2) {
|
|
graphContainer.classList.remove('active');
|
|
return;
|
|
}
|
|
|
|
const data = dataLines.map(line => {
|
|
const [t, ram, vram] = line.split(',');
|
|
return {
|
|
t: parseFloat(t),
|
|
ram: parseFloat(ram),
|
|
vram: vram ? parseFloat(vram) : null
|
|
};
|
|
});
|
|
|
|
const hasVram = data.some(d => d.vram !== null);
|
|
gpuLegend.style.display = hasVram ? 'flex' : 'none';
|
|
|
|
graphContainer.classList.add('active');
|
|
await new Promise(r => setTimeout(r, 10));
|
|
|
|
const ctx = canvas.getContext('2d');
|
|
const dpr = window.devicePixelRatio || 1;
|
|
const rect = canvas.getBoundingClientRect();
|
|
canvas.width = rect.width * dpr;
|
|
canvas.height = rect.height * dpr;
|
|
ctx.scale(dpr, dpr);
|
|
|
|
const w = rect.width;
|
|
const h = rect.height;
|
|
const padding = { top: 10, right: 40, bottom: 20, left: 45 };
|
|
const graphW = w - padding.left - padding.right;
|
|
const graphH = h - padding.top - padding.bottom;
|
|
|
|
const maxRam = Math.max(...data.map(d => d.ram), 0.5);
|
|
const maxVram = hasVram ? Math.max(...data.filter(d => d.vram !== null).map(d => d.vram), 0.5) : 1;
|
|
const maxTime = data[data.length - 1].t;
|
|
|
|
resourceGraphState = { data, padding, w, h, graphW, graphH, maxRam, maxVram, maxTime, hasVram, dpr };
|
|
|
|
drawResourceGraph();
|
|
} catch (e) {
|
|
console.error('Resource graph error:', e);
|
|
graphContainer.classList.remove('active');
|
|
}
|
|
}
|
|
|
|
function drawResourceGraph(hoverX) {
|
|
if (!resourceGraphState) return;
|
|
const { data, padding, w, h, graphW, graphH, maxRam, maxVram, maxTime, hasVram, dpr } = resourceGraphState;
|
|
|
|
const canvas = document.getElementById('resource-canvas');
|
|
const ctx = canvas.getContext('2d');
|
|
ctx.setTransform(dpr, 0, 0, dpr, 0, 0);
|
|
ctx.clearRect(0, 0, w, h);
|
|
|
|
// Grid lines
|
|
ctx.strokeStyle = '#1c2d44';
|
|
ctx.lineWidth = 0.5;
|
|
for (let i = 1; i < 4; i++) {
|
|
const y = padding.top + (graphH * i / 4);
|
|
ctx.beginPath();
|
|
ctx.moveTo(padding.left, y);
|
|
ctx.lineTo(w - padding.right, y);
|
|
ctx.stroke();
|
|
}
|
|
|
|
// Axes
|
|
ctx.strokeStyle = '#243656';
|
|
ctx.lineWidth = 1;
|
|
ctx.beginPath();
|
|
ctx.moveTo(padding.left, padding.top);
|
|
ctx.lineTo(padding.left, h - padding.bottom);
|
|
ctx.lineTo(w - padding.right, h - padding.bottom);
|
|
ctx.lineTo(w - padding.right, padding.top);
|
|
ctx.stroke();
|
|
|
|
// Left axis: RAM
|
|
ctx.fillStyle = '#3fb950';
|
|
ctx.font = '9px sans-serif';
|
|
ctx.textAlign = 'right';
|
|
const ramMax = Math.ceil(maxRam * 10) / 10;
|
|
ctx.fillText(ramMax.toFixed(1) + ' GB', padding.left - 3, padding.top + 4);
|
|
ctx.fillText('0', padding.left - 3, h - padding.bottom + 4);
|
|
|
|
// Right axis: VRAM (if present)
|
|
if (hasVram) {
|
|
ctx.fillStyle = '#d29922';
|
|
ctx.textAlign = 'left';
|
|
const vramMax = Math.ceil(maxVram * 10) / 10;
|
|
ctx.fillText(vramMax.toFixed(1) + ' GB', w - padding.right + 3, padding.top + 4);
|
|
ctx.fillText('0', w - padding.right + 3, h - padding.bottom + 4);
|
|
}
|
|
|
|
// Time labels
|
|
ctx.fillStyle = '#4a6282';
|
|
ctx.textAlign = 'center';
|
|
ctx.fillText('0s', padding.left, h - padding.bottom + 12);
|
|
ctx.fillText(maxTime.toFixed(0) + 's', w - padding.right, h - padding.bottom + 12);
|
|
|
|
function drawLine(values, maxVal, color) {
|
|
if (values.every(v => v === null || isNaN(v))) return;
|
|
ctx.strokeStyle = color;
|
|
ctx.lineWidth = 1.5;
|
|
ctx.beginPath();
|
|
let started = false;
|
|
data.forEach((d, i) => {
|
|
const val = values[i];
|
|
if (val === null || isNaN(val)) return;
|
|
const x = padding.left + (d.t / maxTime) * graphW;
|
|
const y = padding.top + (1 - val / maxVal) * graphH;
|
|
if (!started) { ctx.moveTo(x, y); started = true; }
|
|
else { ctx.lineTo(x, y); }
|
|
});
|
|
ctx.stroke();
|
|
}
|
|
|
|
drawLine(data.map(d => d.ram), ramMax, '#3fb950');
|
|
if (hasVram) {
|
|
drawLine(data.map(d => d.vram), Math.ceil(maxVram * 10) / 10, '#d29922');
|
|
}
|
|
|
|
// Hover crosshair
|
|
if (hoverX !== undefined && hoverX >= padding.left && hoverX <= w - padding.right) {
|
|
const timeAtCursor = ((hoverX - padding.left) / graphW) * maxTime;
|
|
let closest = data[0], closestDist = Infinity;
|
|
for (const d of data) {
|
|
const dist = Math.abs(d.t - timeAtCursor);
|
|
if (dist < closestDist) { closestDist = dist; closest = d; }
|
|
}
|
|
|
|
const snapX = padding.left + (closest.t / maxTime) * graphW;
|
|
|
|
// Vertical line
|
|
ctx.strokeStyle = 'rgba(230,237,243,0.2)';
|
|
ctx.lineWidth = 1;
|
|
ctx.beginPath();
|
|
ctx.moveTo(snapX, padding.top);
|
|
ctx.lineTo(snapX, h - padding.bottom);
|
|
ctx.stroke();
|
|
|
|
// Readout
|
|
ctx.font = '10px sans-serif';
|
|
ctx.textAlign = 'left';
|
|
const readoutX = snapX + 6;
|
|
let readoutY = padding.top + 14;
|
|
|
|
ctx.fillStyle = '#8ba3c1';
|
|
ctx.fillText(closest.t.toFixed(1) + 's', readoutX, readoutY);
|
|
readoutY += 13;
|
|
|
|
ctx.fillStyle = '#3fb950';
|
|
ctx.fillText('RAM: ' + closest.ram.toFixed(2) + ' GB', readoutX, readoutY);
|
|
readoutY += 13;
|
|
|
|
if (hasVram && closest.vram !== null) {
|
|
ctx.fillStyle = '#d29922';
|
|
ctx.fillText('VRAM: ' + closest.vram.toFixed(2) + ' GB', readoutX, readoutY);
|
|
}
|
|
}
|
|
}
|
|
|
|
// Canvas hover handler
|
|
document.getElementById('resource-canvas').addEventListener('mousemove', function(e) {
|
|
if (!resourceGraphState) return;
|
|
const rect = this.getBoundingClientRect();
|
|
drawResourceGraph(e.clientX - rect.left);
|
|
});
|
|
document.getElementById('resource-canvas').addEventListener('mouseleave', function() {
|
|
drawResourceGraph();
|
|
});
|
|
|
|
function closeImgOverlay() {
|
|
const overlay = document.getElementById('img-overlay');
|
|
overlay.classList.remove('active', 'zoomed');
|
|
}
|
|
|
|
function closeLightbox() {
|
|
if (playInterval) {
|
|
clearInterval(playInterval);
|
|
playInterval = null;
|
|
document.getElementById('video-play-btn').innerHTML = '▶ Play';
|
|
}
|
|
closeImgOverlay();
|
|
document.getElementById('resource-graph').classList.remove('active');
|
|
document.getElementById('lightbox').classList.remove('active');
|
|
history.replaceState(null, '', window.location.pathname);
|
|
|
|
if (inIframe) {
|
|
window.parent.postMessage({ type: 'comfytest-close' }, '*');
|
|
}
|
|
}
|
|
|
|
document.getElementById('lightbox').onclick = (e) => {
|
|
if (e.target.id === 'lightbox') closeLightbox();
|
|
};
|
|
|
|
function navigateLightbox(delta) {
|
|
if (workflowNames.length === 0) return;
|
|
const idx = workflowNames.indexOf(currentWorkflow);
|
|
if (idx === -1) return;
|
|
const newIdx = (idx + delta + workflowNames.length) % workflowNames.length;
|
|
openLightboxByName(workflowNames[newIdx]);
|
|
}
|
|
|
|
function handleKey(key) {
|
|
const overlay = document.getElementById('img-overlay');
|
|
if (key === 'Escape') {
|
|
if (overlay.classList.contains('active')) {
|
|
closeImgOverlay();
|
|
} else {
|
|
closeLightbox();
|
|
}
|
|
return;
|
|
}
|
|
if (document.getElementById('lightbox').classList.contains('active') && !overlay.classList.contains('active')) {
|
|
if (key === 'ArrowLeft') { navigateLightbox(-1); }
|
|
if (key === 'ArrowRight') { navigateLightbox(1); }
|
|
if ((key === 'ArrowUp' || key === 'ArrowDown') && inIframe) {
|
|
window.parent.postMessage({
|
|
type: 'comfytest-platform-shift',
|
|
delta: key === 'ArrowUp' ? -1 : 1,
|
|
workflow: currentWorkflow,
|
|
}, '*');
|
|
}
|
|
}
|
|
}
|
|
|
|
document.onkeydown = (e) => {
|
|
if (['Escape', 'ArrowLeft', 'ArrowRight', 'ArrowUp', 'ArrowDown'].includes(e.key)) {
|
|
e.preventDefault();
|
|
handleKey(e.key);
|
|
}
|
|
};
|
|
|
|
// Click lightbox image -> open in fullscreen overlay (fit mode)
|
|
document.getElementById('lightbox-img').addEventListener('click', function(e) {
|
|
e.stopPropagation();
|
|
const overlay = document.getElementById('img-overlay');
|
|
const overlayImg = document.getElementById('img-overlay-content');
|
|
overlayImg.src = this.src;
|
|
overlay.classList.add('active');
|
|
overlay.classList.remove('zoomed');
|
|
});
|
|
|
|
// Click overlay image: fit -> zoomed -> close
|
|
document.getElementById('img-overlay-content').addEventListener('click', function(e) {
|
|
e.stopPropagation();
|
|
const overlay = document.getElementById('img-overlay');
|
|
if (overlay.classList.contains('zoomed')) {
|
|
closeImgOverlay();
|
|
} else {
|
|
overlay.classList.add('zoomed');
|
|
}
|
|
});
|
|
|
|
// Click overlay background -> close overlay
|
|
document.getElementById('img-overlay').addEventListener('click', function(e) {
|
|
if (e.target === this) closeImgOverlay();
|
|
});
|
|
|
|
function openFromHash() {
|
|
const hash = decodeURIComponent(window.location.hash.slice(1));
|
|
if (hash && workflowData[hash]) {
|
|
const w = workflowData[hash];
|
|
openLightbox(w.src, w.title, w.status, w.duration, w.log, w.hardware);
|
|
}
|
|
}
|
|
|
|
window.addEventListener('hashchange', openFromHash);
|
|
window.addEventListener('load', openFromHash);
|
|
|
|
// Listen for messages from parent frames
|
|
window.addEventListener('message', function(e) {
|
|
if (!e.data || !e.data.type) return;
|
|
if (e.data.type === 'comfytest-open' && e.data.name) {
|
|
openLightboxByName(e.data.name);
|
|
}
|
|
if (e.data.type === 'comfytest-key') {
|
|
handleKey(e.data.key);
|
|
}
|
|
});
|
|
|
|
// Detect iframe: hide header and move meta chips into summary
|
|
if (inIframe) {
|
|
document.body.classList.add('in-iframe');
|
|
const chips = document.querySelector('.meta-chips');
|
|
const summary = document.querySelector('.summary');
|
|
if (chips && summary) {
|
|
const wrapper = document.createElement('div');
|
|
wrapper.className = 'summary-meta';
|
|
while (chips.firstChild) wrapper.appendChild(chips.firstChild);
|
|
summary.insertBefore(wrapper, summary.firstChild);
|
|
}
|
|
}
|
|
</script>
|
|
</body>
|
|
</html>
|