14 changed files with 184 additions and 112 deletions
--- a/.gitignore
+++ b/.gitignore
@ -3,22 +3,6 @@ __pycache__/
 *.py[cod]
 *$py.class
 # C extensions
 *.so
 # Specific file
 report.xlsx
 # Distribution / packaging
 output/
 .Python
 # PyBuilder
 .pybuilder/
 target/
 =======
 # Virtual environments
 venv/
 env/
@ -39,6 +23,17 @@ dist/
 # Jupyter Notebook checkpoints
 .ipynb_checkpoints/
 # MyPy cache
 .mypy_cache/
 # PyTest cache
 .pytest_cache/
 # Coverage reports
 htmlcov/
 .coverage
 .coverage.*
 .cache
 # IDE and editor files
 .vscode/
--- a/.idea/inspectionProfiles/profiles_settings.xml
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@ -0,0 +1,6 @@
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+++ b/.idea/misc.xml
@ -0,0 +1,7 @@
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--- a/.idea/modules.xml
+++ b/.idea/modules.xml
@ -0,0 +1,8 @@
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--- a/.idea/new-plate.iml
+++ b/.idea/new-plate.iml
@ -0,0 +1,10 @@
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@ -0,0 +1,6 @@
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@ -0,0 +1,98 @@
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--- a/73
+++ b/73
@ -1,73 +0,0 @@
 Apache License
 Version 2.0, January 2004
 http://www.apache.org/licenses/
 TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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--- a/README.md
+++ b/README.md
@ -1,11 +1,9 @@
-# 🚀 New-Plate
+# 🚀 Helmet Violation Detector
 A **real-time helmet violation detection system** that identifies motorcycles, detects whether riders are wearing helmets, and reads license plates using **YOLO, PaddleOCR, and OpenCV**.
 ---
 ### 📦 `Python 3.12 or below` is required for program compilation
 ## 📌 Features
 - 🏍️ **Motorcycle Detection** (YOLO-based)
@ -24,7 +22,7 @@ A **real-time helmet violation detection system** that identifies motorcycles, d
 ### 1️⃣ Clone the Repository
 ```bash
-git clone https://forge.bitmutex.com/bigwiz/new-plate
+git clone https://github.com/yourusername/helmet-violation-detector.git
 cd helmet-violation-detector
 ```
@ -45,7 +43,7 @@ Ensure you have **Python 3.8+** installed. Then, run:
 pip install -r requirements.txt
 ```
-📌 **Troubleshooting** : 
+**🔹 Note:**
 1. If you face **PaddleOCR-related dependency issues**, make sure to install **paddlepaddle**:
 ```bash
@ -111,3 +109,32 @@ pip install -r requirements.txt
 ```
 ---
 ## 📌 Troubleshooting
 ### ❓ Facing PaddleOCR Issues?
 If you get errors related to `protobuf` or `paddleocr`, try:
 ```bash
 pip install paddlepaddle
 ```
 or
 ```bash
 pip install protobuf==3.20.*
 ```
 ---
 ## 📜 License
 This project is licensed under the **Apache 2.0 License**.
 ---
 ## 👨‍💻 Author
 Developed by **Bitmutex Technologies** 🚀
--- a/main.py
+++ b/main.py
@ -31,7 +31,7 @@ CAMERA_SOURCE = 1 #Webcam / Camera Source REMEMBER WINDOWS HAS WEBCAM ACCESS ISS
 # Load YOLO models
 motorcycle_model = YOLO("models/yolov8n.pt")  # Pretrained COCO model (motorcycles)
 helmet_model = YOLO("models/helmetYoloV8_25epochs.pt")  # Custom helmet detection model
-plate_model = YOLO("models/license_plate_detector1.pt")  # Custom license plate detection model
+plate_model = YOLO("models/license_plate_detector.pt")  # Custom license plate detection model
 # Initialize OCR
 ocr = PaddleOCR(use_angle_cls=True, lang='en')  # Angle correction enabled
@ -39,7 +39,7 @@ ocr = PaddleOCR(use_angle_cls=True, lang='en')  # Angle correction enabled
 # Define Colors
 COLOR_MOTORCYCLE = (0, 255, 0)  # Green
 COLOR_NO_HELMET = (0, 0, 255)  # Red
-COLOR_LICENSE_PLATE = (255, 0, 0)  # Blue
+COLOR_LICENSE_PLATE = (0, 0, 255)  # Red
 #Report Filepath
 EXCEL_FILE = "report.xlsx"
@ -173,7 +173,7 @@ class RealTimeProcessor(QThread):
                break
            # Process the frame
-            processed_frame, license_plate_text = self.parent.process_image(frame, is_video=True)
+            processed_frame, _ = self.parent.process_image(frame, is_video=True)
            # Emit signal to update UI
            self.frame_processed.emit(processed_frame)
@ -579,7 +579,6 @@ class HelmetDetectionApp(QWidget):
        # Format the Excel file
        format_excel(EXCEL_FILE)
    def process_image(self, image_path, is_video=False, output_folder="output/"):
        # 🖼️ Handle video frames directly
@ -682,21 +681,12 @@ class HelmetDetectionApp(QWidget):
                    # Convert BGR to RGB (PaddleOCR expects RGB)
                    plate_roi_rgb = cv2.cvtColor(plate_roi_denoised, cv2.COLOR_GRAY2RGB)
                    # Perform OCR with PaddleOCR
                    result = ocr.ocr(plate_roi_rgb, cls=True)
                    print("Raw Result:", result)
-                    # Perform OCR with PaddleOCR
+                    # Extract text from PaddleOCR result
-                    result = ocr.ocr(plate_roi_rgb, cls=True)
+                    if result and len(result[0]) > 0:
                    print("Raw OCR Result:", result)
                    # Ensure result is valid
                    if result is None or not isinstance(result, list) or len(result) == 0:
                        print("⚠️ OCR result is None or empty!")
                        license_plate_text = "N/A"  # Set default value
                    elif isinstance(result[0], list) and len(result[0]) > 0:
                        print("✅ OCR detected text.")
                        license_plate_text = " ".join([entry[1][0] for entry in result[0]])  # Extract text
                        print("🚗 Detected Plate:", license_plate_text)
@ -707,9 +697,7 @@ class HelmetDetectionApp(QWidget):
                        cv2.rectangle(image, (mx1 + px1, my1 + py1), (mx1 + px2, my1 + py2), COLOR_LICENSE_PLATE, 2)
                        cv2.putText(image, f"Plate: {license_plate_text}", (mx1 + px1, my1 + py1 - 10),
                                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLOR_LICENSE_PLATE, 2)
-                    else:
+
                        print("⚠️ OCR result does not contain expected text format!")
                        license_plate_text = "N/A"  # Set default value
        # 📁 Save processed image for single-image mode
        os.makedirs(output_folder, exist_ok=True)
--- a/models/license_plate_detector1.pt
+++ b/models/license_plate_detector1.pt
--- a/output/processed_D9Zw2BFUwAAdRG6.jpg
+++ b/output/processed_D9Zw2BFUwAAdRG6.jpg
--- a/output/processed_test21.jpg
+++ b/output/processed_test21.jpg
--- a/report.xlsx
+++ b/report.xlsx