initial commit

app.py

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+import gradio as gr
+import torch
+import argparse
+import git
+
+git.Repo.clone_from("https://github.com/timroelofs123/face_reaging.git", "./face_reaging")
+git.Repo.clone_from("https://huggingface.co/timroelofs123/face_re-aging", "./hf")
+
+import sys
+sys.path.append("./face_reaging")
+
+from model.models import UNet
+from scripts.test_functions import process_image
+
+
+model_path = "hf/best_unet_model.pth"
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+unet_model = UNet().to(device)
+unet_model.load_state_dict(torch.load(model_path))
+unet_model.eval()
+
+def block(image, source_age, target_age):
+    return process_image(unet_model, image, video=False, source_age=source_age,
+                         target_age=target_age, window_size=512, stride=256)
+
+demo = gr.Interface(
+    fn=block,
+    inputs=[
+        gr.Image(type="pil"),
+        gr.Slider(10, 90, value=20, step=1, label="Current age", info="Choose your current age"),
+        gr.Slider(10, 90, value=80, step=1, label="Target age", info="Choose the age you want to become")
+    ],
+    outputs="image",
+    examples=[
+        ['assets/gradio_example_images/1.png', 20, 80],
+        ['assets/gradio_example_images/2.png', 75, 40],
+        ['assets/gradio_example_images/3.png', 30, 70],
+        ['assets/gradio_example_images/4.png', 22, 60],
+        ['assets/gradio_example_images/5.png', 28, 75],
+        ['assets/gradio_example_images/6.png', 35, 15]
+    ],
+)
+
+demo.launch()

requirements.txt

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+torch
+torchvision
+antialiased_cnns
+numpy
+face_recognition
+tempfile
+gitpython