Create app.py

app.py

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+import gradio as gr
+from PIL import Image, ImageDraw
+import sys
+import os
+import time
+import threading
+import logging
+
+# Set up logging configuration
+logging.basicConfig(level=logging.INFO)
+
+# Add the backend app to the system path for imports
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../..')))
+
+# Import models
+from yolo import FractureDetector
+from llama import generate_response_based_on_yolo
+
+# Define model path and output folder relative to the app's directory
+MODEL_PATH = 'yolov8n_custom.pkl'  # Update this to the relative path of your model on Hugging Face Spaces
+OUTPUT_FOLDER = '/app/output_images'  # Default output folder in Hugging Face Spaces
+
+# Ensure the output folder exists
+os.makedirs(OUTPUT_FOLDER, exist_ok=True)
+
+# Initialize the fracture detector
+detector = FractureDetector(MODEL_PATH, OUTPUT_FOLDER)
+
+def delete_file_after_delay(file_path, delay):
+    """Delete the specified file after a given delay."""
+    def delete_file():
+        time.sleep(delay)
+        try:
+            os.remove(file_path)
+            logging.info(f"Temporary file {file_path} has been deleted.")
+        except Exception as e:
+            logging.error(f"Error deleting temporary file: {e}")
+
+    thread = threading.Thread(target=delete_file)
+    thread.start()
+
+def mark_fracture_area(image, detections):
+    """Draw bounding boxes on the image based on detected fractures."""
+    draw = ImageDraw.Draw(image)
+    for detection in detections:
+        x1, y1, x2, y2 = map(int, detection['coordinates'])
+        draw.rectangle([x1, y1, x2, y2], outline="red", width=3)
+    return image
+
+def analyze_image(input_image):
+    """Analyze the uploaded image for fractures and generate a report."""
+    # Save the uploaded image to a temporary location
+    temp_image_path = os.path.join(OUTPUT_FOLDER, 'temp_uploaded_image.jpg')
+    input_image.save(temp_image_path)
+
+    try:
+        # Perform fracture detection
+        detections = detector.detect_fractures(temp_image_path, conf_threshold=0.25)
+
+        # Mark the fracture areas on the image
+        marked_image = mark_fracture_area(input_image.copy(), detections)
+
+        # Generate analysis report
+        analysis_report = generate_response_based_on_yolo(detections)
+
+        # Schedule deletion of the temporary file after 2 minutes
+        delete_file_after_delay(temp_image_path, 120)
+
+        return marked_image, analysis_report
+
+    except Exception as e:
+        logging.error(f"An error occurred during analysis: {str(e)}")
+        return input_image, f"An error occurred during analysis: {str(e)}"
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=analyze_image,
+    inputs=gr.Image(type="pil", label="Upload X-ray Image"),
+    outputs=[
+        gr.Image(type="pil", label="Output Image with Marked Fractures"),
+        gr.Textbox(label="Fracture Analysis Report")
+    ],
+    title="Fracture Detection and Analysis System",
+    description="Upload an X-ray image to detect fractures, view marked areas, and receive a detailed analysis report."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    iface.launch()