Create app.py

app.py

@@ -0,0 +1,38 @@
+from fastapi import FastAPI, UploadFile, File
+from transformers import pipeline
+from PIL import Image
+import io
+
+# Initialize the FastAPI app
+app = FastAPI()
+
+# Load the YOLOv5 model for object detection
+detector = pipeline('object-detection', model='ultralytics/yolov5')
+
+@app.post("/detect_objects/")
+async def detect_objects(file: UploadFile = File(...)):
+    # Read image from uploaded file
+    image_bytes = await file.read()
+    image = Image.open(io.BytesIO(image_bytes))
+    
+    # Perform object detection
+    results = detector(image)
+    
+    # Extract bounding box coordinates and labels
+    bounding_boxes = []
+    for result in results:
+        box = result['box']
+        bbox = {
+            'label': result['label'],
+            'confidence': result['score'],
+            'x_min': box['xmin'],
+            'y_min': box['ymin'],
+            'x_max': box['xmax'],
+            'y_max': box['ymax']
+        }
+        bounding_boxes.append(bbox)
+    
+    # Return bounding box coordinates as response
+    return {"bounding_boxes": bounding_boxes}
+
+# To run the server, use: uvicorn app:app --reload