Add MedImageInsight Gradio app

app.py

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+import gradio as gr
+import base64
+import io
+from PIL import Image
+from medimageinsight import MedImageInsight
+
+classifier = MedImageInsight(
+    model_dir="2024.09.27",
+    vision_model_name="medimageinsigt-v1.0.0.pt",
+    language_model_name="language_model.pth"
+)
+classifier.load_model()
+
+
+def analyze(image: Image.Image, labels_str: str):
+    labels = [l.strip() for l in labels_str.split(",") if l.strip()]
+    if not labels:
+        return {}
+    buf = io.BytesIO()
+    image.save(buf, format="PNG")
+    img_b64 = base64.encodebytes(buf.getvalue()).decode("utf-8")
+    results = classifier.predict([img_b64], labels)
+    return results[0]
+
+
+demo = gr.Interface(
+    fn=analyze,
+    inputs=[
+        gr.Image(type="pil", label="Medical Image"),
+        gr.Textbox(
+            value="normal, Pneumonia, pleural effusion",
+            label="Labels (comma-separated)"
+        ),
+    ],
+    outputs=gr.Label(num_top_classes=5, label="Classification Scores"),
+    title="MedImageInsight — Zero-Shot Medical Image Classification",
+    description="Upload a medical image (X-ray, CT, MRI, etc.) and provide candidate labels for zero-shot classification.",
+)
+
+demo.launch()

requirements.txt

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+git+https://huggingface.co/lion-ai/MedImageInsights
+huggingface_hub
+Pillow
+torch