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https://git.datalinker.icu/kijai/ComfyUI-KJNodes.git
synced 2025-12-09 21:04:41 +08:00
cleanup prints
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@ -761,8 +761,6 @@ for example:
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# Remove the last comma and newline
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prompt_string = prompt_string.rstrip(",\n")
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print(prompt_string)
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return (tracked, prompt_string, width, height, bbox_width, bbox_height)
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class AppendInstanceDiffusionTracking:
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@ -894,7 +892,6 @@ CreateInstanceDiffusionTracking -node.
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def draw(self, image, tracking, box_line_width, draw_text, font, font_size):
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import matplotlib.cm as cm
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print(image.shape)
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modified_images = []
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@ -794,7 +794,6 @@ nodes for example.
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mask_image = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3).clone()
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color_list = list(map(int, mask_color.split(', ')))
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print(color_list[0])
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mask_image[:, :, :, 0] = color_list[0] // 255 # Red channel
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mask_image[:, :, :, 1] = color_list[1] // 255 # Green channel
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mask_image[:, :, :, 2] = color_list[2] // 255 # Blue channel
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@ -114,7 +114,6 @@ to a different frame count.
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}
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def scaleschedule(self, old_frame_count, input_str, new_frame_count):
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print("input_str:", input_str)
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pattern = r'"(\d+)"\s*:\s*"(.*?)"(?:,|\Z)'
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frame_strings = dict(re.findall(pattern, input_str))
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@ -134,7 +133,6 @@ to a different frame count.
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# Format the output string
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output_str = ', '.join([f'"{k}":"{v}"' for k, v in sorted(new_frame_strings.items())])
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print(output_str)
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return (output_str,)
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@ -601,7 +599,6 @@ Converts any type to a string.
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if isinstance(input, (int, float, bool)):
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stringified = str(input)
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elif isinstance(input, list):
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print("input is a list")
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stringified = ', '.join(str(item) for item in input)
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else:
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return
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@ -712,10 +709,8 @@ To see node id's, enable node id display from Manager badge menu.
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def get_widget_value(self, id, widget_name, extra_pnginfo, prompt, return_all=False):
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workflow = extra_pnginfo["workflow"]
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print(workflow)
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results = []
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for node in workflow["nodes"]:
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print(node)
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node_id = node["id"]
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if node_id != id:
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@ -1236,8 +1231,8 @@ https://huggingface.co/stabilityai/sv3d
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azimuths.append(interpolated_azimuth)
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elevations.append(interpolated_elevation)
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print("azimuths", azimuths)
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print("elevations", elevations)
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#print("azimuths", azimuths)
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#print("elevations", elevations)
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# Structure the final output
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final_positive = [[pooled, {"concat_latent_image": t, "elevation": elevations, "azimuth": azimuths}]]
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@ -1320,13 +1315,12 @@ https://huggingface.co/roborovski/superprompt-v1
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model = T5ForConditionalGeneration.from_pretrained(checkpoint_path, device_map=device)
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model.to(device)
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input_text = instruction_prompt + ": " + prompt
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print(input_text)
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
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outputs = model.generate(input_ids, max_new_tokens=max_new_tokens)
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out = (tokenizer.decode(outputs[0]))
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out = out.replace('<pad>', '')
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out = out.replace('</s>', '')
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print(out)
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return (out, )
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@ -1391,7 +1385,7 @@ or a .txt file with RealEstate camera intrinsics and coordinates, in a 3D plot.
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poses = f.readlines()
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w2cs = [np.asarray([float(p) for p in pose.strip().split(' ')[7:]]).reshape(3, 4) for pose in poses[1:]]
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fxs = [float(pose.strip().split(' ')[1]) for pose in poses[1:]]
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print(poses)
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#print(poses)
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elif cameractrl_poses is not None:
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poses = cameractrl_poses
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w2cs = [np.array(pose[7:]).reshape(3, 4) for pose in cameractrl_poses]
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