xinyun/ComfyUI-KJNodes
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cleanup prints

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kijai 2024-05-05 18:22:33 +03:00
parent 11459bb550
commit 9acc603b3e
3 changed files with 4 additions and 14 deletions
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3
nodes/curve_nodes.py
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@ -761,8 +761,6 @@ for example:
# Remove the last comma and newline # Remove the last comma and newline
prompt_string = prompt_string.rstrip(",\n") prompt_string = prompt_string.rstrip(",\n")
print(prompt_string)
return (tracked, prompt_string, width, height, bbox_width, bbox_height) return (tracked, prompt_string, width, height, bbox_width, bbox_height)
class AppendInstanceDiffusionTracking: class AppendInstanceDiffusionTracking:
@ -894,7 +892,6 @@ CreateInstanceDiffusionTracking -node.
def draw(self, image, tracking, box_line_width, draw_text, font, font_size): def draw(self, image, tracking, box_line_width, draw_text, font, font_size):
import matplotlib.cm as cm import matplotlib.cm as cm
print(image.shape)
modified_images = [] modified_images = []

1
nodes/image_nodes.py
View File

@ -794,7 +794,6 @@ nodes for example.
mask_image = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3).clone() mask_image = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3).clone()
color_list = list(map(int, mask_color.split(', '))) color_list = list(map(int, mask_color.split(', ')))
print(color_list[0])
mask_image[:, :, :, 0] = color_list[0] // 255 # Red channel mask_image[:, :, :, 0] = color_list[0] // 255 # Red channel
mask_image[:, :, :, 1] = color_list[1] // 255 # Green channel mask_image[:, :, :, 1] = color_list[1] // 255 # Green channel
mask_image[:, :, :, 2] = color_list[2] // 255 # Blue channel mask_image[:, :, :, 2] = color_list[2] // 255 # Blue channel

14
nodes/nodes.py
View File

@ -114,7 +114,6 @@ to a different frame count.
} }
def scaleschedule(self, old_frame_count, input_str, new_frame_count): def scaleschedule(self, old_frame_count, input_str, new_frame_count):
print("input_str:", input_str)
pattern = r'"(\d+)"\s*:\s*"(.*?)"(?:,|\Z)' pattern = r'"(\d+)"\s*:\s*"(.*?)"(?:,|\Z)'
frame_strings = dict(re.findall(pattern, input_str)) frame_strings = dict(re.findall(pattern, input_str))
@ -134,7 +133,6 @@ to a different frame count.
# Format the output string # Format the output string
output_str = ', '.join([f'"{k}":"{v}"' for k, v in sorted(new_frame_strings.items())]) output_str = ', '.join([f'"{k}":"{v}"' for k, v in sorted(new_frame_strings.items())])
print(output_str)
return (output_str,) return (output_str,)
@ -601,7 +599,6 @@ Converts any type to a string.
if isinstance(input, (int, float, bool)): if isinstance(input, (int, float, bool)):
stringified = str(input) stringified = str(input)
elif isinstance(input, list): elif isinstance(input, list):
print("input is a list")
stringified = ', '.join(str(item) for item in input) stringified = ', '.join(str(item) for item in input)
else: else:
return return
@ -712,10 +709,8 @@ To see node id's, enable node id display from Manager badge menu.
def get_widget_value(self, id, widget_name, extra_pnginfo, prompt, return_all=False): def get_widget_value(self, id, widget_name, extra_pnginfo, prompt, return_all=False):
workflow = extra_pnginfo["workflow"] workflow = extra_pnginfo["workflow"]
print(workflow)
results = [] results = []
for node in workflow["nodes"]: for node in workflow["nodes"]:
print(node)
node_id = node["id"] node_id = node["id"]
if node_id != id: if node_id != id:
@ -1236,8 +1231,8 @@ https://huggingface.co/stabilityai/sv3d
azimuths.append(interpolated_azimuth) azimuths.append(interpolated_azimuth)
elevations.append(interpolated_elevation) elevations.append(interpolated_elevation)
print("azimuths", azimuths) #print("azimuths", azimuths)
print("elevations", elevations) #print("elevations", elevations)
# Structure the final output # Structure the final output
final_positive = [[pooled, {"concat_latent_image": t, "elevation": elevations, "azimuth": azimuths}]] final_positive = [[pooled, {"concat_latent_image": t, "elevation": elevations, "azimuth": azimuths}]]
@ -1320,13 +1315,12 @@ https://huggingface.co/roborovski/superprompt-v1
model = T5ForConditionalGeneration.from_pretrained(checkpoint_path, device_map=device) model = T5ForConditionalGeneration.from_pretrained(checkpoint_path, device_map=device)
model.to(device) model.to(device)
input_text = instruction_prompt + ": " + prompt input_text = instruction_prompt + ": " + prompt
print(input_text)
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device) input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
outputs = model.generate(input_ids, max_new_tokens=max_new_tokens) outputs = model.generate(input_ids, max_new_tokens=max_new_tokens)
out = (tokenizer.decode(outputs[0])) out = (tokenizer.decode(outputs[0]))
out = out.replace('<pad>', '') out = out.replace('<pad>', '')
out = out.replace('</s>', '') out = out.replace('</s>', '')
print(out)
return (out, ) return (out, )
@ -1391,7 +1385,7 @@ or a .txt file with RealEstate camera intrinsics and coordinates, in a 3D plot.
poses = f.readlines() poses = f.readlines()
w2cs = [np.asarray([float(p) for p in pose.strip().split(' ')[7:]]).reshape(3, 4) for pose in poses[1:]] w2cs = [np.asarray([float(p) for p in pose.strip().split(' ')[7:]]).reshape(3, 4) for pose in poses[1:]]
fxs = [float(pose.strip().split(' ')[1]) for pose in poses[1:]] fxs = [float(pose.strip().split(' ')[1]) for pose in poses[1:]]
print(poses) #print(poses)
elif cameractrl_poses is not None: elif cameractrl_poses is not None:
poses = cameractrl_poses poses = cameractrl_poses
w2cs = [np.array(pose[7:]).reshape(3, 4) for pose in cameractrl_poses] w2cs = [np.array(pose[7:]).reshape(3, 4) for pose in cameractrl_poses]