app.py

import gradio as gr
import model1 as m1
import model2 as m2

cars = []
lps = []
lp_texts = []
counter = 0

# this is the main function that passes the images to the model 1
def model1(image):    
    global cars, lps, lp_texts, counter
    (cars, lps, lp_texts) = m1.run([image])
    counter = 0
    return cars[0], lps[0], lp_texts[0]

# this is the main function that passes the images to the model 1
def model2(image):    
    global lps, lp_texts, counter
    (lps, lp_texts) = m2.run([image])
    counter = 0
    return lps[0], lp_texts[0]

# this is the main function that passes the images to the model 1
def model3(image):    
    global cars, lps, lp_texts, counter
    (cars, lps, lp_texts) = m3.run([image])
    counter = 0
    return cars[0], lps[0], lp_texts[0]

# function to go to next detected car licence plate
def next_img():
    global counter
    counter += 1
    index =  int(counter % len(cars))
    return cars[index], lps[index], lp_texts[index]

# function to go to prev detected car licence plate
def prev_img():
    global counter
    counter -= 1
    index =  int(counter % len(cars))
    return cars[index], lps[index], lp_texts[index]


# function to go to next detected licence plate
def next_img_lp():
    global counter
    counter += 1
    index =  int(counter % len(lps))
    return lps[index], lp_texts[index]

# function to go to prev detected  licence plate
def prev_img_lp():
    global counter
    counter -= 1
    index =  int(counter % len(lps))
    return lps[index], lp_texts[index]

# this code is responcible for the front end part of the page
with gr.Blocks() as demo:
    gr.Markdown("## ANPR Project")
    with gr.Tab("Model 1"):
        gr.Markdown("Using 3 different ML models")
        gr.Markdown("YOLOv8n for car dection + YOLOv8n for LP detection + easy ocr for text detection")
        img = gr.Image(label="Input")
        submit = gr.Button(value="submit")
        
        with gr.Row():       
            car = gr.Image(label="Car")
            lp = gr.Image(label="Licence Plate")
            lp_text = gr.Text(label="Plate Number")    
            
        with gr.Row():
            next = gr.Button(value="next")
            prev = gr.Button(value="prev")
        
        submit.click(model1, inputs=[img], outputs=[car, lp, lp_text])
        next.click(next_img, outputs=[car, lp, lp_text])
        prev.click(prev_img, outputs=[car, lp, lp_text])
    
    with gr.Tab("Model 2"):
        gr.Markdown("Using 2 different ML models")
        gr.Markdown("YOLOv8m for car dection + easy ocr for text detection")
        gr.Markdown("YOLOv8m for car dection is trained on a large dataset of 25K training images")
        img2 = gr.Image(label="Input")
        submit2 = gr.Button(value="submit")
        
        with gr.Row():       
            lp2 = gr.Image(label="Licence Plate")
            lp_text2 = gr.Text(label="Plate Number")    
            
        with gr.Row():
            next2 = gr.Button(value="next")
            prev2 = gr.Button(value="prev")
        
        submit2.click(model2, inputs=[img2], outputs=[lp2, lp_text2])
        next2.click(next_img_lp, outputs=[lp2, lp_text2])
        prev2.click(prev_img_lp, outputs=[lp2, lp_text2])

demo.launch(share=False)