nodes/kijai-ComfyUI-LivePortraitKJ
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Merge pull request #101 from Quasimondo/patch-2

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Update to KeypointsToImage
This commit is contained in:
Jukka Seppänen
2024-07-28 13:50:24 +02:00
committed by GitHub
parent 451c2f9f02 906cbf6e2f
commit 3493b6aab6
1 changed files with 34 additions and 9 deletions
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nodes.py
+34 -9
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@@ -729,6 +729,7 @@ class KeypointsToImage:
def INPUT_TYPES(s):
return {"required": {
"crop_info": ("CROPINFO", {"default": []}),
"draw_lines": ("BOOLEAN", {"default": False}),
},
}
@@ -737,20 +738,45 @@ class KeypointsToImage:
FUNCTION = "drawkeypoints"
CATEGORY = "LivePortrait"
def drawkeypoints(self, crop_info):
height, width = crop_info["crop_info_list"][0]['input_image_size']
def drawkeypoints(self, crop_info, draw_lines):
# left upper eye | left lower eye | right upper eye | right lower eye | upper lip top | lower lip bottom | upper lip bottom | lower lip top | jawline | left eyebrow | right eyebrow | nose | left pupil | right pupil | nose center
indices = [ 12, 24, 37, 48, 66, 85, 96, 108, 145, 165, 185, 197, 198, 199, 203]
colorlut = [(0, 0, 255), (0, 255, 0), (0, 0, 255), (0, 255, 0), (255, 0, 0), (255, 0, 255), (255, 255, 0), (0, 255, 255), (128, 128, 128), (128, 128, 0), (128, 128, 0), (0,128,128), (255, 255,255), (255, 255,255), (255,255,255)]
colors = []
c = 0
for i in range(203):
if i == indices[c]:
c+=1
colors.append(colorlut[c])
try:
height, width = crop_info["crop_info_list"][0]['input_image_size']
except:
height, width = 512, 512
keypoints_img_list = []
pbar = comfy.utils.ProgressBar(len(crop_info))
for crop in crop_info["crop_info_list"]:
if crop:
keypoints = crop['lmk_crop'].copy()
# Draw each landmark as a circle
blank_image = np.zeros((height, width, 3), dtype=np.uint8) * 255
for (x, y) in keypoints:
# Ensure the coordinates are within the dimensions of the blank image
if 0 <= x < width and 0 <= y < height:
cv2.circle(blank_image, (int(x), int(y)), radius=2, color=(0, 0, 255))
if draw_lines:
start_idx = 0
for end_idx in indices:
color = colors[start_idx]
for i in range(start_idx, end_idx - 1):
pt1 = tuple(map(int, keypoints[i]))
pt2 = tuple(map(int, keypoints[i+1]))
if all(0 <= c < d for c, d in zip(pt1 + pt2, (width, height) * 2)):
cv2.line(blank_image, pt1, pt2, color, thickness=1)
if end_idx == start_idx +1:
x,y = keypoints[start_idx]
cv2.circle(blank_image, (int(x), int(y)), radius=1, thickness=-1, color=colors[start_idx])
start_idx = end_idx
else:
for index, (x, y) in enumerate(keypoints):
cv2.circle(blank_image, (int(x), int(y)), radius=1, thickness=-1, color=colors[index])
keypoints_image = cv2.cvtColor(blank_image, cv2.COLOR_BGR2RGB)
else:
keypoints_image = np.zeros((height, width, 3), dtype=np.uint8) * 255
@@ -760,7 +786,6 @@ class KeypointsToImage:
keypoints_img_tensor = (
torch.stack([torch.from_numpy(np_array) for np_array in keypoints_img_list]) / 255).float()
return (keypoints_img_tensor,)
class KeypointScaler: