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app.py

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+import gradio as gr
+import model1 as m1
+
+cars = []
+lps = []
+lp_texts = []
+counter = 0
+def greet(image):
+    global cars, lps, lp_texts
+    (cars, lps, lp_texts) = m1.run([image])
+    print(len(cars), len(lps), len(lp_texts))
+    return cars[0], lps[0], lp_texts[0]
+
+def next_img():
+    global counter
+    counter += 1
+    index =  int(counter % len(cars))
+    print(index)
+    return cars[index], lps[index], lp_texts[index]
+
+def prev_img():
+    global counter
+    counter -= 1
+    index =  int(counter % len(cars))
+    print(index)
+    return cars[index], lps[index], lp_texts[index]
+
+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(greet, 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")
+
+demo.launch(share=False)

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b8201fecc45f066f02d5653cc587a27fd2d2b543568f08865736137d20b76718
+size 6242670

model1.py

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+from ultralytics import YOLO
+import cv2
+import easyocr
+import numpy as np
+
+car_detection = YOLO("yolov8n.pt")
+lp_detection = YOLO('best.pt')
+reader = easyocr.Reader(['en'])
+
+# inputs = [cv2.imread('img2.png')]
+
+def run(inputs):
+    counter = 0
+    input = inputs[0]
+    # detecting cars
+    car_results = car_detection.predict(source=input, classes=[2], conf=0.6)
+    cars = []
+    lps = []
+    lp_texts = []
+    for car_result in car_results:
+        # print(car_result.boxes)
+        boxes = car_result.boxes.xyxy.tolist()
+        # print(boxes)
+        for box in boxes:
+            # detecting LP of each car
+            car = input[int(box[1]):int(box[3]), int(box[0]):int(box[2])]
+
+            # cv2.imwrite(f'car{counter}.png', car)
+
+            lp_results = lp_detection.predict(source=car, conf=0.6)
+            lp_boxes = lp_results[0].boxes.xyxy.tolist()
+
+            lp = None
+            text = "not found"
+            for lp_box in lp_boxes:
+                lp = car[int(lp_box[1]):int(lp_box[3]), int(lp_box[0]):int(lp_box[2])]
+                lps.append(lp)
+                plate = reader.readtext(lp)
+                
+                text='not found'
+                if len(plate) > 0:
+                    text = plate[0][1]                                   
+                    # cv2.imwrite(f'car{counter}_lp_{text}.png', lp)
+                else:
+                    pass
+                    # cv2.imwrite(f'car{counter}_lp.png', lp)
+                    
+            lp_texts.append(text)                
+            if lp is None:
+                lps.append(np.zeros((100,100,3), np.uint8))
+                
+            counter += 1
+            
+            cars.append(car)
+
+    return cars, lps, lp_texts
+

models/large_LP_YOLOm_best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b9600657c811e290bf3c92f0270c8c182d3ff57fa961a5e5bb82e6136ca1cb1b
+size 207513151

yolov8m_llp.py

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+from ultralytics import YOLO
+
+model = YOLO("models/large_LP_YOLOm_best.pt")

yolov8n.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:31e20dde3def09e2cf938c7be6fe23d9150bbbe503982af13345706515f2ef95
+size 6534387