Create app.py

app.py

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+from transformers import DetrImageProcessor, DetrForObjectDetection
+from PIL import Image, ImageDraw, ImageFont
+import torch
+import gradio as gr
+
+# Load model and processor
+model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
+
+# Load labels
+labels = model.config.id2label
+
+def detect_objects(image):
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+
+    target_sizes = torch.tensor([image.size[::-1]])
+    results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]
+
+    draw = ImageDraw.Draw(image)
+    font = ImageFont.load_default()
+
+    for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
+        box = [round(i, 2) for i in box.tolist()]
+        draw.rectangle(box, outline="red", width=2)
+        draw.text((box[0], box[1] - 10), f"{labels[label.item()]}: {round(score.item(), 2)}", fill="red", font=font)
+
+    return image
+
+gr.Interface(fn=detect_objects, 
+             inputs=gr.Image(type="pil"), 
+             outputs=gr.Image(type="pil"),
+             title="What’s This? - Object Recognition",
+             description="Upload an image to detect objects using DETR").launch()