v1

.dockerignore

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+.venv
+__pycache__
+README.md

.gitignore

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+.venv
+__pycache__

Dockerfile

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+FROM python:3.12
+
+RUN apt-get update && \
+    apt-get install -y \
+    tesseract-ocr \
+    libtesseract-dev \
+    libgl1
+
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+COPY src/ .
+
+EXPOSE 8501
+
+CMD ["streamlit", "run", "main.py"]

requirements.txt

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+altair==5.5.0
+attrs==25.3.0
+blinker==1.9.0
+cachetools==5.5.2
+certifi==2025.1.31
+charset-normalizer==3.4.1
+click==8.1.8
+gitdb==4.0.12
+GitPython==3.1.44
+idna==3.10
+imutils==0.5.4
+Jinja2==3.1.6
+jsonschema==4.23.0
+jsonschema-specifications==2024.10.1
+MarkupSafe==3.0.2
+narwhals==1.31.0
+numpy==2.2.4
+opencv-python==4.11.0.86
+packaging==24.2
+pandas==2.2.3
+pillow==11.1.0
+protobuf==5.29.3
+pyarrow==19.0.1
+pydeck==0.9.1
+pytesseract==0.3.13
+python-dateutil==2.9.0.post0
+pytz==2025.1
+referencing==0.36.2
+requests==2.32.3
+rpds-py==0.23.1
+six==1.17.0
+smmap==5.0.2
+streamlit==1.43.2
+tenacity==9.0.0
+toml==0.10.2
+tornado==6.4.2
+typing_extensions==4.12.2
+tzdata==2025.1
+urllib3==2.3.0
+watchdog==6.0.0

src/image_detection.py

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+import numpy as np
+import cv2
+import pytesseract
+
+def extract_number_plate_text(image):
+    # Convert PIL image to OpenCV format
+    image = np.array(image)
+    gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+
+    # Apply preprocessing
+    filtered = cv2.bilateralFilter(gray, 11, 17, 17)  # Noise reduction
+    edged = cv2.Canny(filtered, 30, 200)  # Edge detection
+
+    # Find contours
+    contours, _ = cv2.findContours(edged, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+    contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]
+
+    plate_text = "No plate detected"
+
+    # Loop over contours to find the number plate
+    for contour in contours:
+        perimeter = cv2.arcLength(contour, True)
+        approx = cv2.approxPolyDP(contour, 0.02 * perimeter, True)
+
+        if len(approx) == 4:  # Possible number plate
+            x, y, w, h = cv2.boundingRect(approx)
+            plate_region = gray[y:y+h, x:x+w]
+
+            # Preprocessing for OCR
+            plate_region = cv2.threshold(plate_region, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
+
+            # Extract text using Tesseract
+            plate_text = pytesseract.image_to_string(plate_region, config="--psm 8").strip()
+            break
+
+    return plate_text

src/main.py

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+import streamlit as st
+from image_detection import extract_number_plate_text
+from PIL import Image
+
+st.title("License Plate Recognition App 🚗")
+
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
+
+
+if uploaded_file:
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded image", use_container_width=True)
+    
+    plate_text = extract_number_plate_text(image)
+    st.subheader("Extracted Number Plate: ")
+    st.write(plate_text)