init app
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- app.py +69 -0
- requirements.txt +5 -0
.gitignore
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.idea/
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app.py
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import os
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import gradio as gr
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import numpy as np
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import torch
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from torchvision.utils import make_grid
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from huggingface_hub import snapshot_download
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from zero_dce import enhance_net_nopool
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os.system("pip freeze")
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REPO_ID = "leonelhs/lowlight"
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MODEL_NAME = "Epoch99.pth"
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model = enhance_net_nopool().cpu()
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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snapshot_folder = snapshot_download(repo_id=REPO_ID)
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model_path = os.path.join(snapshot_folder, MODEL_NAME)
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state = torch.load(model_path, map_location=device)
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model.load_state_dict(state)
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def tensor_to_ndarray(tensor, nrow=1, padding=0, normalize=True):
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grid = make_grid(tensor, nrow, padding, normalize)
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return grid.mul(255).add_(0.5).clamp_(0, 255).permute(1, 2, 0).to("cpu", torch.uint8).numpy()
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def inference(image):
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image = (np.asarray(image) / 255.0)
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image = torch.from_numpy(image).float()
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image = image.permute(2, 0, 1)
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image = image.cpu().unsqueeze(0)
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_, enhanced_image, _ = model(image)
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return tensor_to_ndarray(enhanced_image, nrow=8, padding=2, normalize=False)
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title = "Zero-DCE"
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description = r"""
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## Low-Light Image Enhancement using Zero-DCE
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The model improves the quality of images that have poor contrast, low brightness, and suboptimal exposure.
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This is an implementation of <a href='https://github.com/Li-Chongyi/Zero-DCE' target='_blank'>Zero-DCE</a>.
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It has no any particular purpose than start research on AI models.
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"""
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article = r"""
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Questions, doubts, comments, please email 📧 `leonelhs@gmail.com`
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This demo is running on a CPU, if you like this project please make us a donation to run on a GPU or just give us a <a href='https://github.com/leonelhs/Zero-DCE' target='_blank'>Github ⭐</a>
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<a href="https://www.buymeacoffee.com/leonelhs"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=leonelhs&button_colour=FFDD00&font_colour=000000&font_family=Cookie&outline_colour=000000&coffee_colour=ffffff" /></a>
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<center><img src='https://visitor-badge.glitch.me/badge?page_id=zerodce.visitor-badge' alt='visitor badge'></center>
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"""
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demo = gr.Interface(
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inference, [
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gr.Image(type="pil", label="Image low light"),
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], [
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gr.Image(type="numpy", label="Image enhanced")
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],
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title=title,
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description=description,
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article=article)
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demo.queue().launch()
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requirements.txt
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torch>=2.0.1
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zero_dce
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