init app

.gitignore

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+.idea/
+ __pycache__/
+

app.py

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+import os
+from pathlib import Path
+
+import gradio as gr
+from deoldify import device
+from deoldify.device_id import DeviceId
+from deoldify.generators import gen_inference_deep
+from huggingface_hub import snapshot_download
+
+from model_image_colorizer import ImageFilter, ModelImageColorizer
+
+os.system("pip freeze")
+
+device.set(device=DeviceId.CPU)
+
+REPO_ID = "leonelhs/deoldify"
+MODEL_NAME = "ColorizeArtistic_gen"
+
+snapshot_folder = snapshot_download(repo_id=REPO_ID)
+learn = gen_inference_deep(root_folder=Path(snapshot_folder), weights_name=MODEL_NAME)
+image_filter = ImageFilter(learn=learn)
+colorizer = ModelImageColorizer(image_filter)
+
+
+def inference(image):
+    return colorizer.get_colored_image(image, render_factor=35)
+
+
+title = "DeOldify"
+description = r"""
+## Colorize image
+
+This is an implementation of <a href='https://github.com/jantic/DeOldify' target='_blank'>DeOldify</a>.
+It has no any particular purpose than start research on AI models.
+
+"""
+
+article = r"""
+Questions, doubts, comments, please email 📧 `[email protected]`
+
+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/jantic/DeOldify' target='_blank'>Github ⭐</a>
+
+<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>
+
+<center><img src='https://visitor-badge.glitch.me/badge?page_id=deoldify.visitor-badge' alt='visitor badge'></center>
+"""
+
+demo = gr.Interface(
+    inference, [
+        gr.Image(type="pil", label="Image gray scale"),
+    ], [
+        gr.Image(type="pil", label="Image color")
+    ],
+    title=title,
+    description=description,
+    article=article)
+
+demo.queue().launch()

model_image_colorizer.py

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+import torch
+from PIL import Image as PilImage
+
+from deoldify.filters import IFilter, BaseFilter
+from deoldify.visualize import ModelImageVisualizer
+from fastai.basic_train import Learner
+from fastai.vision import normalize_funcs
+
+stats = ([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+
+
+class ImageFilter(BaseFilter):
+    def __init__(self, learn: Learner):
+        super().__init__(learn)
+        self.render_base = 16
+        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+        self.norm, self.denorm = normalize_funcs(*stats)
+
+    def filter(self, filtered_image: PilImage, render_factor=35) -> PilImage:
+        orig_image = filtered_image.copy()
+        render_sz = render_factor * self.render_base
+        model_image = self._model_process(orig=filtered_image, sz=render_sz)
+        raw_color = self._unsquare(model_image, orig_image)
+        return raw_color
+
+
+class ModelImageColorizer(ModelImageVisualizer):
+    def __init__(self, filter: IFilter):
+        self.filter = filter
+
+    def get_colored_image(self, image, render_factor: int = None) -> PilImage:
+        self._clean_mem()
+        return self.filter.filter(image, render_factor=render_factor)

requirements.txt

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+torch>=2.0.1
+torchvision~=0.15.2
+numpy~=1.24.3
+pillow~=9.5.0
+opencv-python
+deoldify~=0.0.1
+
+
+