Create app.py

app.py

@@ -0,0 +1,64 @@
+# app.py
+
+from transformers import pipeline
+import gradio as gr
+from PIL import Image, ImageDraw, ImageFont
+import random
+
+# Load the YOLO-based object detection pipeline
+detector = pipeline("object-detection", model="hustvl/yolos-tiny")
+
+# Generate a random color for each label
+label_colors = {}
+
+def get_color(label):
+    if label not in label_colors:
+        label_colors[label] = (
+            random.randint(0, 255),
+            random.randint(0, 255),
+            random.randint(0, 255)
+        )
+    return label_colors[label]
+
+# Detection function
+def detect_objects(img):
+    results = detector(img)
+    draw = ImageDraw.Draw(img)
+    font = ImageFont.load_default()
+
+    for obj in results:
+        label = obj["label"]
+        score = obj["score"]
+        box = obj["box"]
+        color = get_color(label)
+
+        # Draw bounding box
+        draw.rectangle(
+            [box["xmin"], box["ymin"], box["xmax"], box["ymax"]],
+            outline=color,
+            width=3
+        )
+
+        # Prepare label with confidence
+        label_text = f"{label} ({score:.2f})"
+        text_bbox = draw.textbbox((box["xmin"], box["ymin"]), label_text, font=font)
+        text_background = [text_bbox[0], text_bbox[1], text_bbox[2], text_bbox[3]]
+
+        # Draw background for text
+        draw.rectangle(text_background, fill=color)
+        draw.text((text_bbox[0], text_bbox[1]), label_text, fill="black", font=font)
+
+    return img
+
+# Gradio interface
+interface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="YOLO Object Detection with Color-coded Labels",
+    description="Upload an image. Detected objects are shown with bounding boxes and color-coded labels using YOLOS-Tiny."
+)
+
+if __name__ == "__main__":
+    interface.launch()
+