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app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image, ImageDraw
+
+# Load object detection pipeline
+detector = pipeline("object-detection", model="facebook/detr-resnet-50")
+
+def detect_objects(image):
+    results = detector(image)
+
+    # Draw bounding boxes on the image
+    img = image.copy()
+    draw = ImageDraw.Draw(img)
+
+    for obj in results:
+        box = obj["box"]
+        label = obj["label"]
+        score = obj["score"]
+
+        # Rectangle around object
+        draw.rectangle(
+            [(box["xmin"], box["ymin"]), (box["xmax"], box["ymax"])],
+            outline="red", width=3
+        )
+        # Label text
+        draw.text((box["xmin"], box["ymin"] - 10), f"{label} ({score:.2f})", fill="red")
+
+    return img
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Object Detection App (with Bounding Boxes)")
+
+    with gr.Row():
+        input_img = gr.Image(type="pil", label="Upload an Image")
+        output_img = gr.Image(type="pil", label="Detected Objects")
+
+    btn = gr.Button("Detect Objects")
+    btn.click(fn=detect_objects, inputs=input_img, outputs=output_img)
+
+demo.launch()

requirements.txt

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+gradio>=3.30
+transformers>=4.40
+torch>=1.13