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Deep modification of the RS Outpaint node

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Raykosan
2026-07-30 06:14:49 +03:00
parent 943cc3c869
commit 274f9bf77c
5 changed files with 710 additions and 486 deletions
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Rayko_Outpaint.py
+157 -119
View File
@@ -13,20 +13,16 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import base64
import io
import json
import numpy as np
import server
import torch
import torch.nn.functional as F
from aiohttp import web
from PIL import Image
import time
import os
import folder_paths
import threading
import gc
_GRID = 16
_MIN_DIM = 32
@@ -35,11 +31,12 @@ _DEFAULT_PAD_FACTOR = 0.3
_frame_cache = {}
_PENDING_DECISIONS = {}
_SAVED_CROP_PRESETS = {}
_APPROVED_CROPS = {} # {node_id: {src_hash: crop_state}}
_APPROVED_CROPS = {}
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
PRESET_DIR = os.path.join(CURRENT_DIR, "presets")
def _tensor_hash(tensor):
try:
t = tensor[0] if tensor.dim() == 4 else tensor
@@ -48,6 +45,7 @@ def _tensor_hash(tensor):
except Exception:
return None
def _tensor_to_jpeg(image_tensor):
arr = (image_tensor.cpu().numpy() * 255).clip(0, 255).astype(np.uint8)
img = Image.fromarray(arr)
@@ -55,6 +53,7 @@ def _tensor_to_jpeg(image_tensor):
img.save(buf, format="JPEG", quality=85)
return buf.getvalue()
def _adapt_crop_to_new_size(crop_state, new_w, new_h):
if not crop_state:
return None
@@ -67,7 +66,7 @@ def _adapt_crop_to_new_size(crop_state, new_w, new_h):
cy = max(-new_h, min(cy, new_h - _GRID))
cw = max(_GRID, min(cw, new_w * 2))
ch = max(_GRID, min(ch, new_h * 2))
out_w = parts[4] if len(parts) >= 5 else 0
out_h = parts[5] if len(parts) >= 6 else 0
colors = parts[6:9] if len(parts) >= 9 else [255, 0, 0]
@@ -76,6 +75,7 @@ def _adapt_crop_to_new_size(crop_state, new_w, new_h):
except Exception:
return None
class RSOutpaint:
@classmethod
def INPUT_TYPES(cls):
@@ -101,27 +101,42 @@ class RSOutpaint:
def outpaint_prep(self, image, crop_state, unique_id):
src = image[0] if image.dim() == 4 else image
src_h, src_w, _ = src.shape
if src_w < _MIN_DIM or src_h < _MIN_DIM:
raise ValueError(f"Input image too small ({src_w}×{src_h}).")
unique_id = str(unique_id)
try:
src_hash = _tensor_hash(src)
cached = _frame_cache.get(unique_id, {})
is_new_image = (cached.get("src_hash") != src_hash or
cached.get("width") != src_w or
is_new_image = (cached.get("src_hash") != src_hash or
cached.get("width") != src_w or
cached.get("height") != src_h)
# Проверяем, есть ли утверждённый кроп для этого изображения
approved_crop = _APPROVED_CROPS.get(unique_id, {}).get(src_hash)
saved_preset = _SAVED_CROP_PRESETS.get(unique_id, {})
batch_mode_active = saved_preset.get("active", False)
batch_mode_type = saved_preset.get("mode", "single")
auto_apply = False
if batch_mode_active and saved_preset.get("crop_state"):
if batch_mode_type == "multi":
auto_apply = True
elif batch_mode_type == "single" and not is_new_image:
auto_apply = True
if not auto_apply:
approved_crop = _APPROVED_CROPS.get(unique_id, {}).get(src_hash)
if approved_crop and not is_new_image:
crop_state = approved_crop
auto_apply = True
if auto_apply:
if not batch_mode_active:
pass
else:
crop_state = _adapt_crop_to_new_size(saved_preset["crop_state"], src_w, src_h)
if approved_crop and not is_new_image:
# Используем сохранённый кроп, пропускаем ожидание
crop_state = approved_crop
# Но всё равно отправляем событие на фронтенд, чтобы показать Reset
try:
i = 255. * src.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
@@ -138,98 +153,89 @@ class RSOutpaint:
"image_height": img.height,
"is_new_image": is_new_image,
"src_hash": src_hash,
"already_approved": True # <-- НОВЫЙ ФЛАГ
"auto_approved": True,
"applied_crop_state": crop_state
})
except Exception as e:
except Exception:
pass
else:
if is_new_image:
if unique_id in _frame_cache:
del _frame_cache[unique_id]
if unique_id in _APPROVED_CROPS:
del _APPROVED_CROPS[unique_id]
if unique_id in _SAVED_CROP_PRESETS:
del _SAVED_CROP_PRESETS[unique_id]
crop_state = ""
# Обновляем кеш
_frame_cache[unique_id] = {
"width": src_w,
"height": src_h,
"src_hash": src_hash,
"width": src_w,
"height": src_h,
"src_hash": src_hash,
"image": _tensor_to_jpeg(src)
}
saved_preset = _SAVED_CROP_PRESETS.get(unique_id, {})
batch_mode_active = saved_preset.get("active", False)
if not batch_mode_active:
if unique_id not in _PENDING_DECISIONS:
_PENDING_DECISIONS[unique_id] = {
"status": "pending",
"crop_state": crop_state,
"last_heartbeat": time.time()
}
else:
_PENDING_DECISIONS[unique_id]["status"] = "pending"
_PENDING_DECISIONS[unique_id]["crop_state"] = crop_state
_PENDING_DECISIONS[unique_id]["last_heartbeat"] = time.time()
try:
i = 255. * src.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
filename = f"rsoutpaint_{unique_id}.png"
subfolder = "rsoutpaint"
full_output_folder = os.path.join(folder_paths.get_temp_directory(), subfolder)
os.makedirs(full_output_folder, exist_ok=True)
img.save(os.path.join(full_output_folder, filename))
server.PromptServer.instance.send_sync("rs_outpaint.show", {
"node_id": unique_id,
"image_url": f"/view?filename={filename}&type=temp&subfolder={subfolder}",
"image_width": img.width,
"image_height": img.height,
"is_new_image": is_new_image,
"src_hash": src_hash
})
except Exception as e:
pass
while True:
state = _PENDING_DECISIONS.get(unique_id, {})
current_status = state.get("status", "pending")
current_crop_state = state.get("crop_state", crop_state)
last_hb = state.get("last_heartbeat", time.time())
if current_status == "approved":
crop_state = current_crop_state
if unique_id not in _APPROVED_CROPS:
_APPROVED_CROPS[unique_id] = {}
_APPROVED_CROPS[unique_id][src_hash] = crop_state
break
elif current_status == "cancelled":
return (torch.zeros((1, src_h, src_w, 3)), torch.ones((1, src_h, src_w)), torch.zeros((1, src_h, src_w, 3)), 0, 0)
elif current_status == "removed":
return (image, torch.ones((1, src_h, src_w)), image, src_w, src_h)
elif time.time() - last_hb > 10.0:
return (image, torch.ones((1, src_h, src_w)), image, src_w, src_h)
elif current_status == "rejected":
_PENDING_DECISIONS[unique_id]["status"] = "pending"
crop_state = current_crop_state
time.sleep(0.2)
if unique_id not in _PENDING_DECISIONS:
_PENDING_DECISIONS[unique_id] = {
"status": "pending",
"crop_state": crop_state,
"last_heartbeat": time.time()
}
else:
if saved_preset.get("crop_state"):
crop_state = _adapt_crop_to_new_size(saved_preset["crop_state"], src_w, src_h)
_PENDING_DECISIONS[unique_id]["status"] = "pending"
_PENDING_DECISIONS[unique_id]["crop_state"] = crop_state
_PENDING_DECISIONS[unique_id]["last_heartbeat"] = time.time()
try:
i = 255. * src.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
filename = f"rsoutpaint_{unique_id}.png"
subfolder = "rsoutpaint"
full_output_folder = os.path.join(folder_paths.get_temp_directory(), subfolder)
os.makedirs(full_output_folder, exist_ok=True)
img.save(os.path.join(full_output_folder, filename))
server.PromptServer.instance.send_sync("rs_outpaint.show", {
"node_id": unique_id,
"image_url": f"/view?filename={filename}&type=temp&subfolder={subfolder}",
"image_width": img.width,
"image_height": img.height,
"is_new_image": is_new_image,
"src_hash": src_hash
})
except Exception:
pass
while True:
state = _PENDING_DECISIONS.get(unique_id, {})
current_status = state.get("status", "pending")
current_crop_state = state.get("crop_state", crop_state)
last_hb = state.get("last_heartbeat", time.time())
if current_status == "approved":
crop_state = current_crop_state
if unique_id not in _APPROVED_CROPS:
_APPROVED_CROPS[unique_id] = {}
_APPROVED_CROPS[unique_id][src_hash] = crop_state
break
elif current_status == "cancelled":
if unique_id in _APPROVED_CROPS and src_hash:
_APPROVED_CROPS[unique_id].pop(src_hash, None)
if not _APPROVED_CROPS[unique_id]:
del _APPROVED_CROPS[unique_id]
return (torch.zeros((1, src_h, src_w, 3)), torch.ones((1, src_h, src_w)), torch.zeros((1, src_h, src_w, 3)), 0, 0)
elif current_status == "removed":
return (image, torch.ones((1, src_h, src_w)), image, src_w, src_h)
elif time.time() - last_hb > 10.0:
return (image, torch.ones((1, src_h, src_w)), image, src_w, src_h)
elif current_status == "rejected":
_PENDING_DECISIONS[unique_id]["status"] = "pending"
crop_state = current_crop_state
time.sleep(0.2)
# --- Формирование результата (без изменений) ---
crop_x = crop_y = crop_w = crop_h = 0
output_width = output_height = 0
use_crop_state = False
color_r, color_g, color_b = 255, 0, 0
bg_r, bg_g, bg_b = 20, 20, 20
if crop_state:
try:
parts = [int(v) for v in str(crop_state).split(",")]
@@ -243,7 +249,7 @@ class RSOutpaint:
if len(parts) >= 9:
color_r, color_g, color_b = parts[6], parts[7], parts[8]
if len(parts) >= 12:
bg_r, bg_g, bg_b = parts[9], parts[10], parts[11]
bg_r, bg_g, bg_b = parts[9], parts[10], parts[11]
except ValueError:
pass
@@ -260,11 +266,13 @@ class RSOutpaint:
eff_w = output_width if output_width >= _GRID else crop_w
eff_h = output_height if output_height >= _GRID else crop_h
eff_w = max(eff_w, _GRID)
eff_h = max(eff_h, _GRID)
if eff_w < 32: eff_w = src_w
if eff_h < 32: eff_h = src_h
if eff_w < 32:
eff_w = src_w
if eff_h < 32:
eff_h = src_h
src_np = src.cpu().numpy()
out = np.full((eff_h, eff_w, 3), 0.5, dtype=np.float32)
@@ -288,7 +296,7 @@ class RSOutpaint:
final_dst_y = max(0, min(final_dst_y, eff_h - 1))
copy_w = max(0, min(src_copy_w, eff_w - final_dst_x))
copy_h = max(0, min(src_copy_h, eff_h - final_dst_y))
if copy_w > 0 and copy_h > 0:
src_slice = src_np[src_y_start:src_y_start + copy_h, src_x_start:src_x_start + copy_w]
dst_slice = out[final_dst_y:final_dst_y + copy_h, final_dst_x:final_dst_x + copy_w]
@@ -304,8 +312,8 @@ class RSOutpaint:
control_image = torch.from_numpy(out).unsqueeze(0)
control_mask = torch.from_numpy(mask).unsqueeze(0)
norm_color = torch.tensor([color_r/255.0, color_g/255.0, color_b/255.0]).view(1, 1, 1, 3)
norm_bg = torch.tensor([bg_r/255.0, bg_g/255.0, bg_b/255.0]).view(1, 1, 1, 3)
norm_color = torch.tensor([color_r / 255.0, color_g / 255.0, color_b / 255.0]).view(1, 1, 1, 3)
norm_bg = torch.tensor([bg_r / 255.0, bg_g / 255.0, bg_b / 255.0]).view(1, 1, 1, 3)
mask_exp = control_mask.unsqueeze(3)
mask_image = mask_exp * norm_color + (1.0 - mask_exp) * norm_bg
mask_image = torch.clamp(mask_image, 0.0, 1.0)
@@ -316,9 +324,11 @@ class RSOutpaint:
if unique_id in _PENDING_DECISIONS:
del _PENDING_DECISIONS[unique_id]
NODE_CLASS_MAPPINGS = {"RSOutpaint": RSOutpaint}
NODE_DISPLAY_NAME_MAPPINGS = {"RSOutpaint": "🦊 RS Outpaint"}
@server.PromptServer.instance.routes.post("/rs_outpaint/decision")
async def rs_outpaint_decision(request):
try:
@@ -327,28 +337,22 @@ async def rs_outpaint_decision(request):
decision = data.get("decision")
crop_state = data.get("crop_state")
batch_mode = data.get("batch_mode", False)
src_hash = data.get("src_hash")
batch_type = data.get("batch_type", "single")
if node_id in _PENDING_DECISIONS:
if decision == "approve":
_PENDING_DECISIONS[node_id]["status"] = "approved"
if crop_state:
if crop_state:
_PENDING_DECISIONS[node_id]["crop_state"] = crop_state
_PENDING_DECISIONS[node_id]["batch_mode"] = batch_mode
if batch_mode and crop_state:
_SAVED_CROP_PRESETS[node_id] = {"crop_state": crop_state, "active": True}
if src_hash:
if node_id not in _APPROVED_CROPS:
_APPROVED_CROPS[node_id] = {}
_APPROVED_CROPS[node_id][src_hash] = crop_state
_SAVED_CROP_PRESETS[node_id] = {
"crop_state": crop_state,
"active": True,
"mode": batch_type
}
elif decision == "cancel":
_PENDING_DECISIONS[node_id]["status"] = "cancelled"
if node_id in _APPROVED_CROPS and src_hash:
_APPROVED_CROPS[node_id].pop(src_hash, None)
if not _APPROVED_CROPS[node_id]:
del _APPROVED_CROPS[node_id]
if node_id in _SAVED_CROP_PRESETS:
del _SAVED_CROP_PRESETS[node_id]
return web.Response(status=200, text="OK")
@@ -356,6 +360,7 @@ async def rs_outpaint_decision(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/unapprove")
async def rs_outpaint_unapprove(request):
try:
@@ -370,6 +375,7 @@ async def rs_outpaint_unapprove(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/cleanup")
async def rs_outpaint_cleanup(request):
try:
@@ -380,13 +386,15 @@ async def rs_outpaint_cleanup(request):
_PENDING_DECISIONS[node_id]["last_heartbeat"] = time.time()
if node_id in _APPROVED_CROPS:
del _APPROVED_CROPS[node_id]
# Добавляем очистку кэша фрейма для полной надёжности
if node_id in _frame_cache:
del _frame_cache[node_id]
if node_id in _SAVED_CROP_PRESETS:
del _SAVED_CROP_PRESETS[node_id]
return web.Response(status=200, text="OK")
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/heartbeat")
async def rs_outpaint_heartbeat(request):
try:
@@ -399,24 +407,34 @@ async def rs_outpaint_heartbeat(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/batch_toggle")
async def rs_outpaint_batch_toggle(request):
try:
data = await request.json()
node_id = str(data.get("node_id"))
enabled = data.get("enabled", False)
batch_type = data.get("batch_type", "single")
enabled = data.get("enabled", True)
if node_id in _SAVED_CROP_PRESETS:
_SAVED_CROP_PRESETS[node_id]["active"] = enabled
_SAVED_CROP_PRESETS[node_id]["mode"] = batch_type
elif enabled and node_id in _PENDING_DECISIONS:
crop_state = _PENDING_DECISIONS[node_id].get("crop_state")
if crop_state:
_SAVED_CROP_PRESETS[node_id] = {"crop_state": crop_state, "active": True}
_SAVED_CROP_PRESETS[node_id] = {
"crop_state": crop_state,
"active": True,
"mode": batch_type
}
return web.Response(status=200, text="OK")
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/clear_preset")
async def rs_outpaint_clear_preset(request):
"""Очищает только батч-пресет. Используется в обычном режиме."""
try:
data = await request.json()
node_id = str(data.get("node_id"))
@@ -426,19 +444,35 @@ async def rs_outpaint_clear_preset(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/clear_all")
async def rs_outpaint_clear_all(request):
"""Очищает батч-пресет и кэш утверждённых кропов. Используется после завершения батча."""
try:
data = await request.json()
node_id = str(data.get("node_id"))
if node_id in _SAVED_CROP_PRESETS:
del _SAVED_CROP_PRESETS[node_id]
if node_id in _APPROVED_CROPS:
del _APPROVED_CROPS[node_id]
return web.Response(status=200, text="OK")
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/save_preset")
async def rs_outpaint_save_preset(request):
try:
data = await request.json()
name = data.get("name", "").strip()
if not name:
if not name:
return web.Response(status=400, text="Name required")
name = "".join(c for c in name if c.isalnum() or c in " _-").strip()
if not name:
if not name:
return web.Response(status=400, text="Invalid name")
os.makedirs(PRESET_DIR, exist_ok=True)
filepath = os.path.join(PRESET_DIR, f"{name}.json")
with open(filepath, 'w', encoding='utf-8') as f:
json.dump(data.get("preset_data", {}), f, indent=2)
@@ -446,6 +480,7 @@ async def rs_outpaint_save_preset(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/list_presets")
async def rs_outpaint_list_presets(request):
try:
@@ -456,6 +491,7 @@ async def rs_outpaint_list_presets(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/load_preset")
async def rs_outpaint_load_preset(request):
try:
@@ -469,12 +505,14 @@ async def rs_outpaint_load_preset(request):
except Exception as e:
return web.Response(status=500, text=str(e))
@server.PromptServer.instance.routes.post("/rs_outpaint/delete_preset")
async def rs_outpaint_delete_preset(request):
try:
data = await request.json()
name = data.get("name")
if not name: return web.Response(status=400, text="Name required")
if not name:
return web.Response(status=400, text="Name required")
filepath = os.path.join(PRESET_DIR, f"{name}.json")
if os.path.exists(filepath):
os.remove(filepath)
__init__.py
+1 -1
View File
@@ -29,7 +29,7 @@ IGNORED_MODULES: Set[str] = {'__init__.py'}
REQUIRED_MODULES: Set[str] = set()
PACKAGE_DISPLAY_NAME = "ComfyUI_RaykoStudio"
__version__ = "0.33.0"
__version__ = "0.33.1"
def load_modules():
print(f"🦊 {PACKAGE_DISPLAY_NAME}: Version: {__version__}")
package.json
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "ComfyUI_RaykoStudio",
"version": "0.33.0",
"version": "0.33.1",
"description": "Set of custom nodes for ComfyUI providing additional image processing capabilities",
"author": "Raykosan",
"license": "Apache License 2.0",
pyproject.toml
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "ComfyUI_RaykoStudio"
description = "Set of custom nodes for ComfyUI providing additional image processing capabilities"
version = "0.33.0"
version = "0.33.1"
license = { file = "LICENSE" }
dependencies = ["torch", "numpy", "Pillow>=10.0.0", "freetype-py>=2.5.1", "pycairo>=1.29.0", "scipy>=1.10.0"]
web/rs_outpaint.js
+550 -364
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