Create app.py

app.py

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+# app.py
+import cv2
+import numpy as np
+import gradio as gr
+from ultralytics import YOLO
+import easyocr
+
+# Load YOLOv8 model
+model_path = "YOLOv8n.pt"  # Local path in repo
+yolo_model = YOLO(model_path)
+
+# Initialize EasyOCR
+easyocr_reader = easyocr.Reader(['en'], gpu=False)
+
+def detect_and_read_plate(image_np):
+    results = yolo_model.predict(source=image_np, conf=0.25)
+    boxes = results[0].boxes.xyxy.cpu().numpy().astype(int)
+    
+    annotated_image = image_np.copy()
+    detected_texts = []
+
+    for i, box in enumerate(boxes):
+        x1, y1, x2, y2 = box[:4]
+        cropped_plate = image_np[y1:y2, x1:x2]
+        text_results = easyocr_reader.readtext(cropped_plate)
+
+        plate_texts = []
+        for (bbox, text, conf) in text_results:
+            if conf > 0.3:
+                plate_texts.append(text)
+
+        plate_text = ' '.join(plate_texts)
+        detected_texts.append(f"Plate {i+1}: {plate_text}")
+
+        cv2.rectangle(annotated_image, (x1, y1), (x2, y2), (0, 255, 0), 2)
+        cv2.putText(annotated_image, plate_text, (x1, y1 - 10), 
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 2)
+
+    return annotated_image, '\n'.join(detected_texts)
+
+demo = gr.Interface(
+    fn=detect_and_read_plate,
+    inputs=gr.Image(type="numpy", label="Upload Image"),
+    outputs=[
+        gr.Image(type="numpy", label="Detected Image with Plate Text"),
+        gr.Textbox(label="Detected Plate Texts")
+    ],
+    title="Number Plate Detection and OCR",
+    description="YOLOv8 detects license plates and EasyOCR reads the number."
+)
+
+demo.launch()