Delete app.py

app.py

@@ -1,53 +0,0 @@
-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.")