Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import pipeline
+
+# Initialize the object detection pipeline with the microsoft/table-transformer-detection model
+pipe = pipeline("object-detection", model="microsoft/table-transformer-detection")
+
+# Define the function to detect objects in an image
+def detect_objects(image):
+    result = pipe(image)
+    # Format the result to show detected objects and their scores
+    detections = [{"label": item["label"], "score": item["score"], "box": item["box"]} for item in result]
+    return detections
+
+# Set up the Gradio interface
+app = gr.Interface(
+    fn=detect_objects,                  # Function for object detection
+    inputs=gr.Image(type="filepath"),   # Input field to upload an image
+    outputs=gr.JSON(),                  # Output field for detected objects (JSON format)
+    title="Object Detection",           # Title of the app
+    description="Upload an image to detect objects using Microsoft's Table Transformer model."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch()