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lane detection and curve prediction using histogram equalization techniques, both simple and adaptive.

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LanePrediction

ENPM673 – Perception for Autonomous Robots – Spring 2022

Instructions to Run Programs:

Problem 1: Histogram equalization

Even before running the code, Please goto histogram_adapt_equalization.py line number 99 and change the path to ./Data folder to feed the input images

git clone https://github.com/sumedhreddy90/LaneCurvePrediction.git
cd Code
python3 histogram_adapt_equalization.py

Output:

Histogram Frame: Histogram_frame

Adaptive Histogram Frame: Adaptive_histogram

Comparision between Histogram and AH Adaptive_Histogram_Compare

Problem 2: Straight Lane Detection

cd Code
python3 straight_lane.py

Output

Canny Edge Detection: 2_Canny_Edges Warped Edges: 2_warped Final Straight lane detection 2_straighlane_detected

Problem 3: Predict Turn

cd Code
python3 lane_predict.py

Output

Undistort Frame undistorted Bird eye- Warped Frame warp Detected Lanes - colors mask lanes Final Road lane detection lanes_detected Combined Output combined_result

Link to output video for problem 3: https://drive.google.com/file/d/1DzkIUOs3ekwaCDiMnLvYAXV7RbqTusmu/view?usp=sharing

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