Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+
+# Load a pre-trained object detection model from the transformers library
+# Using 'detr-resnet50' as an example, a powerful object detection model
+try:
+    object_detector = pipeline("object-detection", model="facebook/detr-resnet50")
+except Exception as e:
+    print(f"Error loading model: {e}")
+    print("Please ensure you have an internet connection and sufficient disk space.")
+    object_detector = None # Set to None if model loading fails
+
+def detect_objects_in_image(image):
+    """
+    Performs object detection on the input image.
+
+    Args:
+        image: A PIL Image object.
+
+    Returns:
+        A list of dictionaries, where each dictionary represents a detected object
+        and contains 'box' (bounding box coordinates) and 'label' (object class).
+        Returns a string message if the model failed to load.
+    """
+    if object_detector is None:
+        return "Object detection model failed to load. Cannot process image."
+
+    if image is None:
+        return [] # Return empty list if no image is provided
+
+    # Perform object detection
+    detections = object_detector(image)
+
+    # The pipeline returns a list of dictionaries with 'box' and 'label' keys
+    # Example: [{'box': {'xmin': 125, 'ymin': 138, 'xmax': 309, 'ymax': 403}, 'label': 'remote', 'score': 0.998}]
+    return detections
+
+# Create the Gradio interface
+if object_detector is not None:
+    interface = gr.Interface(
+        fn=detect_objects_in_image,
+        inputs=gr.Image(type="pil", label="Upload an Image"),
+        outputs=gr.Label(num_top_classes=5, label="Detected Objects"), # Using Label to display detections
+        title="Object Detection with Hugging Face and Gradio",
+        description="Upload an image to detect objects using a pre-trained model.",
+        allow_flagging="never"
+    )
+
+    # Launch the Gradio app
+    interface.launch()
+else:
+    print("Gradio interface not launched because the object detection model failed to load.")