added Road Lane Detection

Author: NotIncorecc

Road-Lane-Detection/README.md

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+# Road Lane Detection
+
+This project is a Python program that uses OpenCV to detect lanes on roads. Unlike other lane detection programs, this one dynamically calculates the mask based on the color of the road, making it more adaptable to different environments.
+
+## Features
+
+- **Dynamic Mask Calculation**: Adjusts the mask according to the road color.
+- **Lane Detection**: Identifies and highlights lanes on the road.
+
+## Requirements
+
+- Python 3.x
+- OpenCV
+
+## Acknowledgements
+
+- OpenCV documentation
+- Various online tutorials and resources

Road-Lane-Detection/dik2_1.py

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+import cv2
+import numpy as np
+
+def canny_edge_detection(frame):
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    blur = cv2.GaussianBlur(gray, (5, 5), 0)
+    edges = cv2.Canny(blur, 50, 150)
+    return edges
+
+def detect_road_region(frame):
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    
+    lower_gray = np.array([0, 0, 50])  # Lower bound for gray
+    upper_gray = np.array([180, 50, 200])  # Upper bound for gray
+
+    mask = cv2.inRange(hsv, lower_gray, upper_gray)
+
+    contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+    if contours:
+        largest_contour = max(contours, key=cv2.contourArea)
+
+        epsilon = 0.02 * cv2.arcLength(largest_contour, True)
+        polygon = cv2.approxPolyDP(largest_contour, epsilon, True)
+
+        road_mask = np.zeros_like(mask)
+        if len(polygon) >= 3:  
+            cv2.fillPoly(road_mask, [polygon], 255)
+
+        return road_mask
+    return None
+
+def hough_transform(masked_edges):
+    lines = cv2.HoughLinesP(masked_edges, 2, np.pi / 180, 100, np.array([]), minLineLength=40, maxLineGap=5)
+    return lines
+
+def display_lines(frame, lines):
+    line_image = np.zeros_like(frame)
+    if lines is not None:
+        for line in lines:
+            x1, y1, x2, y2 = line.reshape(4)
+            cv2.line(line_image, (x1, y1), (x2, y2), (0, 255, 0), 10)
+    return line_image
+
+def combine_images(frame, line_image):
+    combined_image = cv2.addWeighted(frame, 0.8, line_image, 1, 1)
+    return combined_image
+
+def process_frame(frame):
+    edges = canny_edge_detection(frame)
+
+    road_mask = detect_road_region(frame)
+
+    if road_mask is not None:
+        masked_edges = cv2.bitwise_and(edges, edges, mask=road_mask)
+    else:
+        masked_edges = edges
+
+    lines = hough_transform(masked_edges)
+
+    line_image = display_lines(frame, lines)
+
+    result = combine_images(frame, line_image)
+
+    return result
+
+vds = ['lane5.mp4']#add more of your own videos here
+
+cap = cv2.VideoCapture('videos/'+vds[0])
+while(cap.isOpened()):
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    result = process_frame(frame)
+    cv2.imshow('Lane Detection', result)
+    road_cont_mask = detect_road_region(frame)
+    cv2.imshow('Lane Detection2', road_cont_mask)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()

Road-Lane-Detection/requirements.txt

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+opencv-python