Create app.py

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+from PIL import Image
+from transformers import pipeline
+from PIL import ImageDraw
+
+object_detector = pipeline("object-detection", model="facebook/detr-resnet-50")
+
+# model_path = "C:\\Users\\abdul\\Documents\\genaiproj\\genai\\Models\\models--facebook--detr-resnet-50\\snapshots\\1d5f47bd3bdd2c4bbfa585418ffe6da5028b4c0b"
+# object_detector = pipeline("object-detection", model=model_path)
+
+def draw_bounding_boxes(image, detections):
+    draw = ImageDraw.Draw(image)
+    
+    for detection in detections:
+        # Extract bounding box coordinates and label
+        box = detection['box']
+        label = detection['label']
+        xmin, ymin, xmax, ymax = box['xmin'], box['ymin'], box['xmax'], box['ymax']
+        
+        # Draw rectangle and label
+        draw.rectangle([xmin, ymin, xmax, ymax], outline="red", width=3)
+        draw.text((xmin, ymin - 10), label, fill="red")
+    
+    return image
+
+
+def detect_object(image):
+    raw_image = Image.open(image)
+    output = object_detector(raw_image)
+    processed_image = draw_bounding_boxes(raw_image, output)
+    return processed_image
+
+# print(output)
+
+gr.close_all()
+
+# demo = gr.Interface(fn=summary, inputs="text", outputs="text")
+
+demo = gr.Interface(
+    fn=detect_object, 
+    inputs=[gr.Image(label="Select Image", type="filepath")], 
+    outputs=[gr.Image(label="Image with Bounding Box", type="pil")], 
+    title="Object Detector", 
+    theme="soft",
+    description="This is an object detection model that detects objects in an image and draws bounding boxes around them.")
+    
+demo.launch(share=True)