Merge pull request recodehive#828 from aviralgarg05/main-2

Vehicle Lane Detection Using Machine Learning and OpenCV

Vehicle Lane Detection Using Machine Learning and OpenCV/README.md

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+# Lane-Line-Detection
+
+
+## Description
+
+Lane-Line-Detection is a project aimed at detecting lane lines in video streams or images using computer vision techniques. This project leverages OpenCV and Python to identify and highlight lane markings, which is a crucial component for autonomous driving systems.
+
+## Table of Contents
+
+- [Usage](#usage)
+- [Contributing](#contributing)
+- [License](#license)
+- [Acknowledgments](#acknowledgments)
+- [Contact](#contact)
+
+
+
+### Prerequisites
+
+Ensure you have the following installed:
+- Python 3.x
+- pip
+
+### Steps
+
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/your_username/Lane-Line-Detection.git
+   cd Lane-Line-Detection
+   ```
+
+2. Install the required packages
+
+## Usage
+
+### Running the Lane Line Detection
+
+1. To detect lane lines in a video:
+   ```bash
+   python lane_detection.py --video_path path/to/your/video.mp4
+   ```
+
+2. To detect lane lines in an image:
+   ```bash
+   python lane_detection.py --image_path path/to/your/image.jpg
+   ```
+
+
+## Contributing
+
+We welcome contributions! Please follow these steps to contribute:
+
+1. Fork the repository.
+2. Create a new branch (`git checkout -b feature-branch`).
+3. Make your changes.
+4. Commit your changes (`git commit -am 'Add new feature'`).
+5. Push to the branch (`git push origin feature-branch`).
+6. Create a new Pull Request.
+
+Please ensure your code adheres to the project's coding standards and includes tests.
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+

Vehicle Lane Detection Using Machine Learning and OpenCV/gui.py

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+import tkinter as tk
+from tkinter import *
+import cv2
+from PIL import Image, ImageTk
+import os
+import numpy as np
+
+
+global last_frame1                                    #creating global              variable
+last_frame1 = np.zeros((480, 640, 3), dtype=np.uint8)
+global last_frame2                                      #creating global      variable
+last_frame2 = np.zeros((480, 640, 3), dtype=np.uint8)
+global cap1
+global cap2
+cap1 = cv2.VideoCapture("./test2.mp4")
+cap2 = cv2.VideoCapture("./test2.mp4")
+
+def show_vid():                                       
+    if not cap1.isOpened():                             
+        print("cant open the camera1")
+    flag1, frame1 = cap1.read()
+    frame1 = cv2.resize(frame1,(600,500))
+    if flag1 is None:
+        print ("Major error!")
+    elif flag1:
+        global last_frame1
+        last_frame1 = frame1.copy()
+        pic = cv2.cvtColor(last_frame1, cv2.COLOR_BGR2RGB)     
+        img = Image.fromarray(pic)
+        imgtk = ImageTk.PhotoImage(image=img)
+        lmain.imgtk = imgtk
+        lmain.configure(image=imgtk)
+        lmain.after(10, show_vid)
+
+
+def show_vid2():
+    if not cap2.isOpened():                             
+        print("cant open the camera2")
+    flag2, frame2 = cap2.read()
+    frame2 = cv2.resize(frame2,(600,500))
+    if flag2 is None:
+        print ("Major error2!")
+    elif flag2:
+        global last_frame2
+        last_frame2 = frame2.copy()
+        pic2 = cv2.cvtColor(last_frame2, cv2.COLOR_BGR2RGB)
+        img2 = Image.fromarray(pic2)
+        img2tk = ImageTk.PhotoImage(image=img2)
+        lmain2.img2tk = img2tk
+        lmain2.configure(image=img2tk)
+        lmain2.after(10, show_vid2)
+
+if __name__ == '__main__':
+    root=tk.Tk()   
+    heading = Label(root,image=img, text="Lane-Line Detection")
+    # heading.configure(background='#CDCDCD',foreground='#364156')
+    heading.pack() 
+    heading2=Label(root,text="Lane-Line Detection",pady=20, font=('arial',45,'bold'))                                 
+    heading2.configure(foreground='#364156')
+    heading2.pack()
+    lmain = tk.Label(master=root)
+    lmain2 = tk.Label(master=root)
+
+    lmain.pack(side = LEFT)
+    lmain2.pack(side = RIGHT)
+    root.title("Lane-line detection")            
+    root.geometry("1250x900+100+10") 
+
+    exitbutton = Button(root, text='Quit',fg="red",command=   root.destroy).pack(side = BOTTOM,)
+    show_vid()
+    show_vid2()
+    root.mainloop()                                  
+    cap.release()