add app.py requirements

app.py

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+import torch
+from PIL import Image, ImageDraw
+from torchvision.transforms import Compose, ToTensor, Normalize
+from transformers import DetrForObjectDetection, DetrImageProcessor
+import gradio as gr
+
+# Load the pre-trained DETR model and processor
+model_name = "facebook/detr-resnet-50"
+model = DetrForObjectDetection.from_pretrained(model_name)
+processor = DetrImageProcessor.from_pretrained(model_name)
+
+# Define fracture detection function
+def detect_fractures(image):
+    """Detect fractures in the given image using DETR."""
+    # Convert the input image to a format suitable for the model
+    inputs = processor(images=image, return_tensors="pt")
+
+    # Perform object detection
+    outputs = model(**inputs)
+
+    # Extract predictions
+    logits = outputs.logits
+    bboxes = outputs.pred_boxes
+    scores = logits.softmax(-1)[..., :-1].max(-1)
+
+    # Filter predictions
+    threshold = 0.5  # confidence threshold
+    keep = scores.values > threshold
+
+    filtered_boxes = bboxes[keep].detach().cpu()
+    filtered_scores = scores.values[keep].detach().cpu().tolist()
+
+    # Convert normalized bounding boxes to absolute coordinates
+    width, height = image.size
+    filtered_boxes = filtered_boxes * torch.tensor([width, height, width, height])
+
+    # Draw bounding boxes on the image
+    draw = ImageDraw.Draw(image)
+    for box, score in zip(filtered_boxes, filtered_scores):
+        x_min, y_min, x_max, y_max = box.tolist()
+        draw.rectangle(((x_min, y_min), (x_max, y_max)), outline="red", width=3)
+        draw.text((x_min, y_min), f"Fracture: {score:.2f}", fill="red")
+
+    return image
+
+# Define Gradio interface
+def infer(image):
+    """Run fracture detection and return the result image."""
+    return detect_fractures(image)
+
+iface = gr.Interface(
+    fn=infer,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="Fracture Detection",
+    description="Upload an X-ray or medical image to detect fractures using DETR.",
+    # examples=["example1.jpg", "example2.jpg"],
+)
+
+iface.launch()

requirements.txt

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+torch
+Pillow
+torchvision
+transformers
+gradio