hf spaces
Browse files- app.py +0 -3
- sd_model.py +3 -0
app.py
CHANGED
@@ -11,8 +11,6 @@ import os
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import numpy as np
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from PIL import Image
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import spaces
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path = os.getcwd()
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output_dir = f"{path}/output"
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input_dir = f"{path}/input"
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@@ -25,7 +23,6 @@ class webui:
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def __init__(self):
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self.demo = gr.Blocks()
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@spaces.GPU
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def undercoat(self, input_image, pos_prompt, neg_prompt, alpha_th):
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org_line_image = input_image
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image = pil2cv(input_image)
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import numpy as np
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from PIL import Image
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path = os.getcwd()
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output_dir = f"{path}/output"
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input_dir = f"{path}/input"
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def __init__(self):
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self.demo = gr.Blocks()
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def undercoat(self, input_image, pos_prompt, neg_prompt, alpha_th):
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org_line_image = input_image
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image = pil2cv(input_image)
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sd_model.py
CHANGED
@@ -2,6 +2,8 @@ from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCM
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from diffusers import StableDiffusionXLControlNetPipeline, ControlNetModel, AutoencoderKL
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import torch
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device = "cuda"
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def get_cn_pipeline():
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@@ -48,6 +50,7 @@ def get_cn_detector(image):
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print(detectors)
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return detectors
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def generate(pipe, detectors, prompt, negative_prompt):
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default_pos = "1girl, bestquality, 4K, ((white background)), no background"
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default_neg = "shadow, (worst quality, low quality:1.2), (lowres:1.2), (bad anatomy:1.2), (greyscale, monochrome:1.4)"
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from diffusers import StableDiffusionXLControlNetPipeline, ControlNetModel, AutoencoderKL
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import torch
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import spaces
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device = "cuda"
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def get_cn_pipeline():
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print(detectors)
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return detectors
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@spaces.GPU
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def generate(pipe, detectors, prompt, negative_prompt):
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default_pos = "1girl, bestquality, 4K, ((white background)), no background"
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default_neg = "shadow, (worst quality, low quality:1.2), (lowres:1.2), (bad anatomy:1.2), (greyscale, monochrome:1.4)"
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