Super-squash branch 'main' using huggingface_hub

.gitattributes

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README.md

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+---
+title: ACE DEMO
+emoji: 📊
+colorFrom: gray
+colorTo: purple
+sdk: gradio
+sdk_version: 6.9.0
+app_file: app.py
+pinned: false
+models:
+  - LexBwmn/ACE-V1
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from ultralytics import YOLO
+import cv2
+import PIL.Image as Image
+import numpy as np
+import os
+from huggingface_hub import hf_hub_download
+
+token = os.getenv("ACE_TOKEN")
+repo_id = "LexBwmn/ACE_LAB"
+
+try:
+    model_path = hf_hub_download(
+        repo_id=repo_id,
+        filename="model.pt",
+        token=token
+    )
+    model = YOLO(model_path)
+except Exception as e:
+    print(f"Error loading private model: {e}")
+    model = None
+
+def predict(img):
+    global model
+    if model is None:
+        return None
+    
+    try:
+        img_array = np.array(img)
+        results = model(img_array, conf=0.466, imgsz=640)     
+        res_plotted = results[0].plot()
+        res_rgb = cv2.cvtColor(res_plotted, cv2.COLOR_BGR2RGB)
+        return Image.fromarray(res_rgb)
+    except Exception as e:
+        print(f"CRITICAL ERROR DURING SUBMIT: {e}")
+        return None
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Upload Brain MRI"), 
+    outputs=gr.Image(type="pil", label="Detection Results"),
+    title="ACE-V1.1 Lab Test",
+    description="Secure Inference Test for Brain Tumor Detection."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+ultralytics
+gradio
+opencv-python
+numpy
+Pillow