Create app.py

app.py

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+import os
+import shutil
+import torch
+import cv2
+import gradio as gr
+from PIL import Image
+
+# Download sample images
+os.makedirs("sample_images", exist_ok=True)
+os.chdir("sample_images")
+os.system("gdown 1LiKfKhksfu8f_A4x-BhOjZgZHADdLdWz -O img1.jpg")
+os.system("gdown 1jJ6uP_bpdnCRqCuiqZjJG8yeexsz6IUp -O img2.jpg")
+os.system("gdown 1usp9c4VcTX2yche5o2WCi7yJw85n_yeZ -O img3.jpg")
+
+os.chdir("../")
+
+
+examples = [['sample_images/img1.jpg', "Cartoonify"],
+            ['sample_images/img2.jpg', "Cartoonify"],
+            ['sample_images/img3.jpg', "Cartoonify"],
+            ]
+
+inference_on = ['Full Resolution Image', 'Downsampled Image']
+
+title = "Face Cartoonify for Video Call Privacy"
+description = """
+Gradio demo for <b>Face Cartoonify for Video Call Privacy</b>.\n 
+"""
+
+article = "<p style='text-align: center'><a href='#'> Face Cartoonify for Video Call Privacy </a> | <a href='#'>Github Repo</a></p>"
+
+model = torch.hub.load(
+    "AK391/animegan2-pytorch:main",
+    "generator",
+    pretrained=True,
+    device="cpu",
+    progress=False
+)
+
+face2paint = torch.hub.load(
+    'AK391/animegan2-pytorch:main', 'face2paint', 
+    size=512, device="cpu",side_by_side=False
+)
+
+def inference(img, method):
+    if not os.path.exists('temp'):
+      os.system('mkdir temp')
+    
+    img.save("temp/image.jpg", "JPEG")
+
+    if method == "Cartoonify AnimeGanV2":
+      out = face2paint(model, img)
+      return out
+    else:
+      os.system("python cartoon.py --input_path 'temp/image.jpg'  --result_dir './temp/'")
+      return 'temp/image.jpg'
+    
+gr.Interface(
+    inference,
+    [
+        gr.inputs.Image(type="pil", label="Input"),
+        gr.inputs.Radio(["Cartoonify OpenCV", "Cartoonify AnimeGanV2"], default="Cartoonify AnimeGanV2", label='Method'),
+
+    ],
+    gr.outputs.Image(type="file", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    theme ="huggingface",
+    examples=examples,
+    allow_flagging=False,
+    ).launch(debug=True,enable_queue=True)