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app.py

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+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+import numpy as np
+
+model = YOLO("runs/segment/train/weights/best.pt")
+
+# Prediction function for image
+def segment_image(image):
+    results = model(image)[0]
+    return np.array(results.plot())
+
+# Prediction function for video
+def segment_video(video_path):
+    results = model(video_path)
+    return results[0].save(save_dir="segmented_video/") or "segmented_video/predict.mp4"
+
+
+with gr.Blocks(theme=gr.themes.Soft(),title='YOLOv11 Image Segmentation') as demo:
+    gr.Markdown("# YOLOv11 Image Segmentation")
+    with gr.Row():
+        img_input = gr.Image(type="pil", label="Upload an Image")
+        img_output = gr.Image(label="Segmented Image")
+    img_button = gr.Button("Segment Image")
+    img_button.click(segment_image, inputs=img_input, outputs=img_output)
+
+    gr.Examples(
+        examples=[
+            "datasets/coco8-seg/images/train/000000000025.jpg",
+            "datasets/coco8-seg/images/train/000000000009.jpg"
+        ],
+        inputs=img_input,
+        outputs=img_output,
+        fn=segment_image,
+        label="Example Images"
+    )
+
+demo.launch(inbrowser=True)
+

requirements.txt

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+gradio
+ultralytics
+Pillow
+numpy