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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() |