學習汽車駕駛技術講座

學習 OpenCV 4、YOLO、道路標記和行人檢測以及自動駕駛汽車的交通標志分類此教程共13小時，中英雙語字幕，畫質清晰無水印，源碼附件齊全！課程英文名：Autonomous Cars The Complete Computer Vision Course 2021

學習汽車駕駛技術講座

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學習汽車駕駛技術講座

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課程內容

課程地址：

隨著世界邁向無人駕駛的未來，在這個新興領域對經驗豐富的工程師和研究人員的需求從未像現在這樣重要。

我們將介紹的工具和算法包括：

深度學習和人工神經網絡。

卷積神經網絡。

1：上車動作左手打開車門 2：右腳先跨入駕駛室內 3：同時身體做到座墊上 4：左腳跟進放在離合下方，左手關車門。5：下車動作左手打開車門 6：左腳邁出駕駛室，同時身體和右腳同時跨出駕駛室。注意事項規范的上下車動作，。

HOG特征提取。

用灰度圖像進行檢測。

色彩空間技術。

學習汽車駕駛技術講座

RGB 空間。

HSV 空間。

http://v.ku6.com/show/KXGVgDTIZhJJLvS2n6Ygwg。html 【祝你成才】汽車駕駛技術視頻講座第8集 http://v.ku6.com/show/smS03CfG-T2hmpDmKr8SzA。html

銳化和模糊。

邊緣檢測和梯度計算。

拉普拉斯邊緣檢測器。

Canny 邊緣檢測。

仿射和投影變換。

圖像平移、旋轉和調整大小。

霍夫變換

KNN 背景減法器。

MOG 背景減法器。

均值偏移。

卡爾曼濾波器。

DeepLabv3+。

如果您準備好迎接全新的挑戰，并了解您在傳統監督機器學習、無監督機器學習甚至深度學習中從未見過的 AI 技術，那么本課程適合您。

檢測道路標記。

道路標志檢測。

檢測行人項目。

冰湖環境。

語義分割。

車輛檢測。

第一項了解儀表盤功能。包括車速表、轉速表、里程表、行程表、燃油表、水溫表、油壓警示燈、制動系統警示燈等。第二項知道調整后視鏡、倒車鏡的基本原則。第三項熟悉并正確使用轉向燈、大燈、雨刮器、喇叭等系統。第四項正。

教程目錄

.├── 5 - Autonomous Cars The Complete Computer Vision Course 2021│ ├── 1. Introduction│ │ ├── 1. Course structure [caiyun-en-zh].srt│ │ ├── 1. Course structure.mp4│ │ ├── 1. Course structure.srt│ │ ├── 10. Benefit of Self-Driving Cars [caiyun-en-zh].srt│ │ ├── 10. Benefit of Self-Driving Cars.mp4│ │ ├── 10. Benefit of Self-Driving Cars.srt│ │ ├── 11. Building the safe systems [caiyun-en-zh].srt│ │ ├── 11. Building the safe systems.mp4│ │ ├── 11. Building the safe systems.srt│ │ ├── 12. Deep learning and computer visionapproaches for Self-Driving Cars [caiyun-en-zh].srt│ │ ├── 12. Deep learning and computer visionapproaches for Self-Driving Cars.mp4│ │ ├── 12. Deep learning and computer visionapproaches for Self-Driving Cars.srt│ │ ├── 13. LIDAR and computer vision for Self-Driving Cars vision [caiyun-en-zh].srt│ │ ├── 13. LIDAR and computer vision for Self-Driving Cars vision.mp4│ │ ├── 13. LIDAR and computer vision for Self-Driving Cars vision.srt│ │ ├── 2. How To Make The Most Out Of This Course [caiyun-en-zh].srt│ │ ├── 2. How To Make The Most Out Of This Course.mp4│ │ ├── 2. How To Make The Most Out Of This Course.srt│ │ ├── 3. What is ANN [caiyun-en-zh].srt│ │ ├── 3. What is ANN.mp4│ │ ├── 3. What is ANN.srt│ │ ├── 4. What is Neuron [caiyun-en-zh].srt│ │ ├── 4. What is Neuron.mp4│ │ ├── 4. What is Neuron.srt│ │ ├── 5. What is Multilayer Neural Network [caiyun-en-zh].srt│ │ ├── 5. What is Multilayer Neural Network.mp4│ │ ├── 5. What is Multilayer Neural Network.srt│ │ ├── 6. What is keras (Optional from AI in Healthcare course) [caiyun-en-zh].srt│ │ ├── 6. What is keras (Optional from AI in Healthcare course).mp4│ │ ├── 6. What is keras (Optional from AI in Healthcare course).srt│ │ ├── 7. Important Terms in this course [caiyun-en-zh].srt│ │ ├── 7. Important Terms in this course.mp4│ │ ├── 7. Important Terms in this course.srt│ │ ├── 8. Important note about tools in this course [caiyun-en-zh].srt│ │ ├── 8. Important note about tools in this course.mp4│ │ ├── 8. Important note about tools in this course.srt│ │ ├── 9. Introduction to Self-Driving Cars [caiyun-en-zh].srt│ │ ├── 9. Introduction to Self-Driving Cars.mp4│ │ └── 9. Introduction to Self-Driving Cars.srt│ ├── 10. Thank you│ │ ├── 1. Thank you [caiyun-en-zh].srt│ │ ├── 1. Thank you.mp4│ │ └── 1. Thank you.srt│ ├── 2. Activation function│ │ ├── 1. What is activation function [caiyun-en-zh].srt│ │ ├── 1. What is activation function.mp4│ │ ├── 1. What is activation function.srt│ │ ├── 2. What is Rectified Linear Unit function [caiyun-en-zh].srt│ │ ├── 2. What is Rectified Linear Unit function.mp4│ │ ├── 2. What is Rectified Linear Unit function.srt│ │ ├── 3. What is Leaky ReLU function [caiyun-en-zh].srt│ │ ├── 3. What is Leaky ReLU function.mp4│ │ ├── 3. What is Leaky ReLU function.srt│ │ ├── 4. What is tanh function [caiyun-en-zh].srt│ │ ├── 4. What is tanh function.mp4│ │ ├── 4. What is tanh function.srt│ │ ├── 5. What is Softmax function [caiyun-en-zh].srt│ │ ├── 5. What is Softmax function.mp4│ │ ├── 5. What is Softmax function.srt│ │ ├── 6. What is The Exponential linear unit function [caiyun-en-zh].srt│ │ ├── 6. What is The Exponential linear unit function.mp4│ │ ├── 6. What is The Exponential linear unit function.srt│ │ ├── 7. What is Swish function [caiyun-en-zh].srt│ │ ├── 7. What is Swish function.mp4│ │ ├── 7. What is Swish function.srt│ │ ├── 8. What is sigmoid function [caiyun-en-zh].srt│ │ ├── 8. What is sigmoid function.mp4│ │ ├── 8. What is sigmoid function.srt│ │ ├── 9. Activation Function Implementation [caiyun-en-zh].srt│ │ ├── 9. Activation Function Implementation.mp4│ │ └── 9. Activation Function Implementation.srt│ ├── 3. Basic Deep Learning Project│ │ ├── 1. Introduction to the project (1) [caiyun-en-zh].srt│ │ ├── 1. Introduction to the project.mp4│ │ ├── 1. Introduction to the project.srt│ │ ├── 10. Saving and loading models [caiyun-en-zh].srt│ │ ├── 10. Saving and loading models.mp4│ │ ├── 10. Saving and loading models.srt│ │ ├── 11. Summary of the project [caiyun-en-zh].srt│ │ ├── 11. Summary of the project.mp4│ │ ├── 11. Summary of the project.srt│ │ ├── 11.1 Udemy_Auto_mpg.ipynb│ │ ├── 2. Importing Data and Libraries [caiyun-en-zh].srt│ │ ├── 2. Importing Data and Libraries.mp4│ │ ├── 2. Importing Data and Libraries.srt│ │ ├── 3. Splitting the dataset into training test and test set [caiyun-en-zh].srt│ │ ├── 3. Splitting the dataset into training test and test set.mp4│ │ ├── 3. Splitting the dataset into training test and test set.srt│ │ ├── 4. Visualizing data [caiyun-en-zh].srt│ │ ├── 4. Visualizing data.mp4│ │ ├── 4. Visualizing data.srt│ │ ├── 5. Standardizing data [caiyun-en-zh].srt│ │ ├── 5. Standardizing data.mp4│ │ ├── 5. Standardizing data.srt│ │ ├── 6. Building and compiling the model [caiyun-en-zh].srt│ │ ├── 6. Building and compiling the model.mp4│ │ ├── 6. Building and compiling the model.srt│ │ ├── 7. Training the model [caiyun-en-zh].srt│ │ ├── 7. Training the model.mp4│ │ ├── 7. Training the model.srt│ │ ├── 8. Predicting new，unseen data [caiyun-en-zh].srt│ │ ├── 8. Predicting new，unseen data.mp4│ │ ├── 8. Predicting new，unseen data.srt│ │ ├── 9. Evaluating the model&39;s performance.mp4│ │ └── 9. Evaluating the model's performance.srt│ ├── 4. Computer vision for Self-driving Cars│ │ ├── 1. Introduction (1) [caiyun-en-zh].srt│ │ ├── 1. Introduction.mp4│ │ ├── 1. Introduction.srt│ │ ├── 10. Introduction to RGB space [caiyun-en-zh].srt│ │ ├── 10. Introduction to RGB space.mp4│ │ ├── 10. Introduction to RGB space.srt│ │ ├── 11. Introduction to HSV space [caiyun-en-zh].srt│ │ ├── 11. Introduction to HSV space.mp4│ │ ├── 11. Introduction to HSV space.srt│ │ ├── 12. Introduction to Color space manipulation [caiyun-en-zh].srt│ │ ├── 12. Introduction to Color space manipulation.mp4│ │ ├── 12. Introduction to Color space manipulation.srt│ │ ├── 13. Implementing Color space manipulation Part 1 [caiyun-en-zh].srt│ │ ├── 13. Implementing Color space manipulation Part 1.mp4│ │ ├── 13. Implementing Color space manipulation Part 1.srt│ │ ├── 14. Implementing Color space manipulation Part 2 [caiyun-en-zh].srt│ │ ├── 14. Implementing Color space manipulation Part 2.mp4│ │ ├── 14. Implementing Color space manipulation Part 2.srt│ │ ├── 15. Implementing Color space manipulation Part 3 [caiyun-en-zh].srt│ │ ├── 15. Implementing Color space manipulation Part 3.mp4│ │ ├── 15. Implementing Color space manipulation Part 3.srt│ │ ├── 15.1 Udemy_Converting_images_from_RGB_to_grayscale.ipynb│ │ ├── 16. Introduction to convolution [caiyun-en-zh].srt│ │ ├── 16. Introduction to convolution.mp4│ │ ├── 16. Introduction to convolution.srt│ │ ├── 17. Introductionto Sharpening and blurring [caiyun-en-zh].srt│ │ ├── 17. Introductionto Sharpening and blurring.mp4│ │ ├── 17. Introductionto Sharpening and blurring.srt│ │ ├── 18. Sharpening and blurring Implementation [caiyun-en-zh].srt│ │ ├── 18. Sharpening and blurring Implementation.mp4│ │ ├── 18. Sharpening and blurring Implementation.srt│ │ ├── 18.1 Udemy_Converting_images_from_RGB_to_grayscale (1).ipynb│ │ ├── 19. Introduction to Edge detection and gradient calculation [caiyun-en-zh].srt│ │ ├── 19. Introduction to Edge detection and gradient calculation.mp4│ │ ├── 19. Introduction to Edge detection and gradient calculation.srt│ │ ├── 2. Computer vision Introduction [caiyun-en-zh].srt│ │ ├── 2. Computer vision Introduction.mp4│ │ ├── 2. Computer vision Introduction.srt│ │ ├── 20. Introduction to Sobel [caiyun-en-zh].srt│ │ ├── 20. Introduction to Sobel.mp4│ │ ├── 20. Introduction to Sobel.srt│ │ ├── 21. Introduction to Laplacian edge detector [caiyun-en-zh].srt│ │ ├── 21. Introduction to Laplacian edge detector.mp4│ │ ├── 21. Introduction to Laplacian edge detector.srt│ │ ├── 22. Canny edge detection [caiyun-en-zh].srt│ │ ├── 22. Canny edge detection.mp4│ │ ├── 22. Canny edge detection.srt│ │ ├── 22.1 Chapter_4_Code_Notebook.ipynb│ │ ├── 23. Application of image transformation [caiyun-en-zh].srt│ │ ├── 23. Application of image transformation.mp4│ │ ├── 23. Application of image transformation.srt│ │ ├── 24. Introduction to Affine and Projective transformation [caiyun-en-zh].srt│ │ ├── 24. Introduction to Affine and Projective transformation.mp4│ │ ├── 24. Introduction to Affine and Projective transformation.srt│ │ ├── 25. Image rotation Implementation [caiyun-en-zh].srt│ │ ├── 25. Image rotation Implementation.mp4│ │ ├── 25. Image rotation Implementation.srt│ │ ├── 26. Image translation Implementation [caiyun-en-zh].srt│ │ ├── 26. Image translation Implementation.mp4│ │ ├── 26. Image translation Implementation.srt│ │ ├── 26.1 Udemy_Converting_images_from_RGB_to_grayscale.ipynb│ │ ├── 27. Image resizing Implementation [caiyun-en-zh].srt│ │ ├── 27. Image resizing Implementation.mp4│ │ ├── 27. Image resizing Implementation.srt│ │ ├── 27.1 Udemy_Converting_images_from_RGB_to_grayscale.ipynb│ │ ├── 28. Introduction to Perspective transformation [caiyun-en-zh].srt│ │ ├── 28. Introduction to Perspective transformation.mp4│ │ ├── 28. Introduction to Perspective transformation.srt│ │ ├── 29. Perspective transformation Implementation [caiyun-en-zh].srt│ │ ├── 29. Perspective transformation Implementation.mp4│ │ ├── 29. Perspective transformation Implementation.srt│ │ ├── 29.1 Udemy_Converting_images_from_RGB_to_grayscale (1).ipynb│ │ ├── 3. Challenges in Computer Vision [caiyun-en-zh].srt│ │ ├── 3. Challenges in Computer Vision.mp4│ │ ├── 3. Challenges in Computer Vision.srt│ │ ├── 30. Cropping，dilating，and eroding an image Implementation [caiyun-en-zh].srt│ │ ├── 30. Cropping，dilating，and eroding an image Implementation.mp4│ │ ├── 30. Cropping，dilating，and eroding an image Implementation.srt│ │ ├── 30.1 Udemy_Converting_images_from_RGB_to_grayscale (2).ipynb│ │ ├── 31. Masking regions of interest [caiyun-en-zh].srt│ │ ├── 31. Masking regions of interest.mp4│ │ ├── 31. Masking regions of interest.srt│ │ ├── 31.1 Udemy_Converting_images_from_RGB_to_grayscale (3).ipynb│ │ ├── 32. Introduction to The Hough transform [caiyun-en-zh].srt│ │ ├── 32. Introduction to The Hough transform.mp4│ │ ├── 32. Introduction to The Hough transform.srt│ │ ├── 33. The Hough transform Implementation [caiyun-en-zh].srt│ │ ├── 33. The Hough transform Implementation.mp4│ │ ├── 33. The Hough transform Implementation.srt│ │ ├── 33.1 The_Hough_transform.ipynb│ │ ├── 34. Summary of the section [caiyun-en-zh].srt│ │ ├── 34. Summary of the section.mp4│ │ ├── 34. Summary of the section.srt│ │ ├── 4. Requirement of Self-Driving Cars [caiyun-en-zh].srt│ │ ├── 4. Requirement of Self-Driving Cars.mp4│ │ ├── 4. Requirement of Self-Driving Cars.srt│ │ ├── 5. Digital representation of an image [caiyun-en-zh].srt│ │ ├── 5. Digital representation of an image.mp4│ │ ├── 5. Digital representation of an image.srt│ │ ├── 6. Converting images from RGB to grayscale [caiyun-en-zh].srt│ │ ├── 6. Converting images from RGB to grayscale.mp4│ │ ├── 6. Converting images from RGB to grayscale.srt│ │ ├── 6.1 Udemy_Converting_images_from_RGB_to_grayscale.ipynb│ │ ├── 6.2 images2-20210319T024702Z-001.zip│ │ ├── 7. Detection with the grayscale image [caiyun-en-zh].srt│ │ ├── 7. Detection with the grayscale image.mp4│ │ ├── 7. Detection with the grayscale image.srt│ │ ├── 7.1 Udemy_Converting_images_from_RGB_to_grayscale (1).ipynb│ │ ├── 8. QUICK FIX Video [caiyun-en-zh].srt│ │ ├── 8. QUICK FIX Video.mp4│ │ ├── 8. QUICK FIX Video.srt│ │ ├── 8.1 Udemy_Converting_images_from_RGB_to_grayscale (1).ipynb│ │ ├── 9. Introduction to the Color space techniques [caiyun-en-zh].srt│ │ ├── 9. Introduction to the Color space techniques.mp4│ │ └── 9. Introduction to the Color space techniques.srt│ ├── 5. Detection of road markings by OpenCV│ │ ├── 1. Introduction to the project [caiyun-en-zh].srt│ │ ├── 1. Introduction to the project.mp4│ │ ├── 1. Introduction to the project.srt│ │ ├── 2. Loading the image using OpenCV and Converting the image into grayscale [caiyun-en-zh].srt│ │ ├── 2. Loading the image using OpenCV and Converting the image into grayscale.mp4│ │ ├── 2. Loading the image using OpenCV and Converting the image into grayscale.srt│ │ ├── 3. Smoothing the image and Implementing Canny Edge detection [caiyun-en-zh].srt│ │ ├── 3. Smoothing the image and Implementing Canny Edge detection.mp4│ │ ├── 3. Smoothing the image and Implementing Canny Edge detection.srt│ │ ├── 3.1 Udemy_road_markings.ipynb│ │ ├── 4. Masking the region of interest [caiyun-en-zh].srt│ │ ├── 4. Masking the region of interest.mp4│ │ ├── 4. Masking the region of interest.srt│ │ ├── 5. Applying bitwise_and [caiyun-en-zh].srt│ │ ├── 5. Applying bitwise_and.mp4│ │ ├── 5. Applying bitwise_and.srt│ │ ├── 6. Applying the Hough transform [caiyun-en-zh].srt│ │ ├── 6. Applying the Hough transform.mp4│ │ ├── 6. Applying the Hough transform.srt│ │ ├── 6.1 Udemy_road_markings (1).ipynb│ │ ├── 7. Optimizing the detected road markings [caiyun-en-zh].srt│ │ ├── 7. Optimizing the detected road markings.mp4│ │ ├── 7. Optimizing the detected road markings.srt│ │ ├── 7.1 Udemy_road_markings (2).ipynb│ │ ├── 8. Detecting road markings in a video [caiyun-en-zh].srt│ │ ├── 8. Detecting road markings in a video.mp4│ │ ├── 8. Detecting road markings in a video.srt│ │ ├── 8.1 Udemy_road_markings_videos.ipynb│ │ ├── 8.2 test2.mp4│ │ ├── 9. Summary of the section [caiyun-en-zh].srt│ │ ├── 9. Summary of the section.mp4│ │ └── 9. Summary of the section.srt│ ├── 6. Road Sign Detection│ │ ├── 1. Introduction to convolution neural network [caiyun-en-zh].srt│ │ ├── 1. Introduction to convolution neural network.mp4│ │ ├── 1. Introduction to convolution neural network.srt│ │ ├── 10. Summary of the project [caiyun-en-zh].srt│ │ ├── 10. Summary of the project.mp4│ │ ├── 10. Summary of the project.srt│ │ ├── 2. Convolution Layers [caiyun-en-zh].srt│ │ ├── 2. Convolution Layers.mp4│ │ ├── 2. Convolution Layers.srt│ │ ├── 3. Pooling Layers [caiyun-en-zh].srt│ │ ├── 3. Pooling Layers.mp4│ │ ├── 3. Pooling Layers.srt│ │ ├── 4. Introduction to the project [caiyun-en-zh].srt│ │ ├── 4. Introduction to the project.mp4│ │ ├── 4. Introduction to the project.srt│ │ ├── 5. Loading data [caiyun-en-zh].srt│ │ ├── 5. Loading data.mp4│ │ ├── 5. Loading data.srt│ │ ├── 5.1 traffic-signs-data-20210225T074843Z-001.zip│ │ ├── 6. Exploring image [caiyun-en-zh].srt│ │ ├── 6. Exploring image.mp4│ │ ├── 6. Exploring image.srt│ │ ├── 7. Data Preperation [caiyun-en-zh].srt│ │ ├── 7. Data Preperation.mp4│ │ ├── 7. Data Preperation.srt│ │ ├── 8. Training model [caiyun-en-zh].srt│ │ ├── 8. Training model.mp4│ │ ├── 8. Training model.srt│ │ ├── 8.1 Udemy_Traffic_sign.ipynb│ │ ├── 9. Model accuracy [caiyun-en-zh].srt│ │ ├── 9. Model accuracy.mp4│ │ ├── 9. Model accuracy.srt│ │ └── 9.1 Udemy_Traffic_sign (1).ipynb│ ├── 7. Detecting Pedestrian Project│ │ ├── 1. Introduction to tracking objects [caiyun-en-zh].srt│ │ ├── 1. Introduction to tracking objects.mp4│ │ ├── 1. Introduction to tracking objects.srt│ │ ├── 10. Implementing pedestrians detection Part 3 [caiyun-en-zh].srt│ │ ├── 10. Implementing pedestrians detection Part 3.mp4│ │ ├── 10. Implementing pedestrians detection Part 3.srt│ │ ├── 11. Implementing pedestrians detection Part 4 [caiyun-en-zh].srt│ │ ├── 11. Implementing pedestrians detection Part 4.mp4│ │ ├── 11. Implementing pedestrians detection Part 4.srt│ │ ├── 11.1 Udemy_Detecting_pedestrian (2).ipynb│ │ ├── 12. Summary of the section [caiyun-en-zh].srt│ │ ├── 12. Summary of the section.mp4│ │ ├── 12. Summary of the section.srt│ │ ├── 2. Background subtraction [caiyun-en-zh].srt│ │ ├── 2. Background subtraction.mp4│ │ ├── 2. Background subtraction.srt│ │ ├── 3. MOG background subtractor [caiyun-en-zh].srt│ │ ├── 3. MOG background subtractor.mp4│ │ ├── 3. MOG background subtractor.srt│ │ ├── 3.1 Udemy_MOG_background_subtractor.ipynb│ │ ├── 3.2 hallway.mpg│ │ ├── 4. KNN background subtractor [caiyun-en-zh].srt│ │ ├── 4. KNN background subtractor.mp4│ │ ├── 4. KNN background subtractor.srt│ │ ├── 4.1 Udemy_KNN_background_subtractor.ipynb│ │ ├── 4.2 traffic.flv│ │ ├── 5. Detecting pedestrians Introduction [caiyun-en-zh].srt│ │ ├── 5. Detecting pedestrians Introduction.mp4│ │ ├── 5. Detecting pedestrians Introduction.srt│ │ ├── 6. MeanShift Introduction [caiyun-en-zh].srt│ │ ├── 6. MeanShift Introduction.mp4│ │ ├── 6. MeanShift Introduction.srt│ │ ├── 7. Kalman filter [caiyun-en-zh].srt│ │ ├── 7. Kalman filter.mp4│ │ ├── 7. Kalman filter.srt│ │ ├── 7.1 Udemy_Detecting_pedestrian.ipynb│ │ ├── 8. Implementing pedestrians detection Part 1 [caiyun-en-zh].srt│ │ ├── 8. Implementing pedestrians detection Part 1.mp4│ │ ├── 8. Implementing pedestrians detection Part 1.srt│ │ ├── 9. Implementing pedestrians detection Part 2 [caiyun-en-zh].srt│ │ ├── 9. Implementing pedestrians detection Part 2.mp4│ │ ├── 9. Implementing pedestrians detection Part 2.srt│ │ └── 9.1 Udemy_Detecting_pedestrian (1).ipynb│ ├── 8. Semantic Segmentation│ │ ├── 1. Introduction to semantic segmentation [caiyun-en-zh].srt│ │ ├── 1. Introduction to semantic segmentation.mp4│ │ ├── 1. Introduction to semantic segmentation.srt│ │ ├── 10. Semantic segmentation Implementation Part 1 [caiyun-en-zh].srt│ │ ├── 10. Semantic segmentation Implementation Part 1.mp4│ │ ├── 10. Semantic segmentation Implementation Part 1.srt│ │ ├── 11. Semantic segmentation Implementation Part 2 [caiyun-en-zh].srt│ │ ├── 11. Semantic segmentation Implementation Part 2.mp4│ │ ├── 11. Semantic segmentation Implementation Part 2.srt│ │ ├── 12. Semantic segmentation Implementation Part 3 [caiyun-en-zh].srt│ │ ├── 12. Semantic segmentation Implementation Part 3.mp4│ │ ├── 12. Semantic segmentation Implementation Part 3.srt│ │ ├── 12.1 Udemy_Semantic_Segmentation.ipynb│ │ ├── 13. Semantic segmentation Implementation Part 4 [caiyun-en-zh].srt│ │ ├── 13. Semantic segmentation Implementation Part 4.mp4│ │ ├── 13. Semantic segmentation Implementation Part 4.srt│ │ ├── 13.1 enet-cityscapes.zip│ │ ├── 14. Semantic segmentation Implementation Part 5 [caiyun-en-zh].srt│ │ ├── 14. Semantic segmentation Implementation Part 5.mp4│ │ ├── 14. Semantic segmentation Implementation Part 5.srt│ │ ├── 14.1 Udemy_Semantic_Segmentation.ipynb│ │ ├── 15. Summary of the section [caiyun-en-zh].srt│ │ ├── 15. Summary of the section.mp4│ │ ├── 15. Summary of the section.srt│ │ ├── 2. Semantic Segmentation Achitecture [caiyun-en-zh].srt│ │ ├── 2. Semantic Segmentation Achitecture.mp4│ │ ├── 2. Semantic Segmentation Achitecture.srt│ │ ├── 3. Different Semantic Segmentation Architectures [caiyun-en-zh].srt│ │ ├── 3. Different Semantic Segmentation Architectures.mp4│ │ ├── 3. Different Semantic Segmentation Architectures.srt│ │ ├── 4. U-NET [caiyun-en-zh].srt│ │ ├── 4. U-NET.mp4│ │ ├── 4. U-NET.srt│ │ ├── 5. SegNet [caiyun-en-zh].srt│ │ ├── 5. SegNet.mp4│ │ ├── 5. SegNet.srt│ │ ├── 6. Encoder and Decoder [caiyun-en-zh].srt│ │ ├── 6. Encoder and Decoder.mp4│ │ ├── 6. Encoder and Decoder.srt│ │ ├── 7. Pyramid Scene Parsing Network [caiyun-en-zh].srt│ │ ├── 7. Pyramid Scene Parsing Network.mp4│ │ ├── 7. Pyramid Scene Parsing Network.srt│ │ ├── 8. DeepLabv3+ [caiyun-en-zh].srt│ │ ├── 8. DeepLabv3+.mp4│ │ ├── 8. DeepLabv3+.srt│ │ ├── 9. E-Net [caiyun-en-zh].srt│ │ ├── 9. E-Net.mp4│ │ └── 9. E-Net.srt│ └── 9. Vehicle Detection│ ├── 1. Introduction [caiyun-en-zh].srt│ ├── 1. Introduction.mp4│ ├── 1. Introduction.srt│ ├── 2. What makes YOLO different [caiyun-en-zh].srt│ ├── 2. What makes YOLO different.mp4│ ├── 2. What makes YOLO different.srt│ ├── 3. The YOLO loss function [caiyun-en-zh].srt│ ├── 3. The YOLO loss function.mp4│ ├── 3. The YOLO loss function.srt│ ├── 4. The YOLO architecture [caiyun-en-zh].srt│ ├── 4. The YOLO architecture.mp4│ ├── 4. The YOLO architecture.srt│ ├── 5. YOLO Implementation Part 1 [caiyun-en-zh].srt│ ├── 5. YOLO Implementation Part 1.mp4│ ├── 5. YOLO Implementation Part 1.srt│ ├── 5.1 yolo.h5│ ├── 5.2 coco_classes.txt│ ├── 5.3 images3-20210325T032710Z-001.zip│ ├── 5.4 Udemy_Image_YOLO_Implementation.ipynb│ ├── 6. YOLO Implementation Part 2 [caiyun-en-zh].srt│ ├── 6. YOLO Implementation Part 2.mp4│ ├── 6. YOLO Implementation Part 2.srt│ ├── 6.1 Udemy_YOLO_detection_video.ipynb│ └── 6.2 video_sample.mp4└── 5.txt11 directories，399 files

工具/原料1.一輛長途汽車2.駕校場地道路3.一輛長途汽車步驟/方法4.在平坦的道路上起步:在汽車啟動前掛上安全帶先踩離合踏板到底。5:將鑰匙轉到點火位置點燃發動機換到一檔。6:此時打開轉向燈。同時注意后視鏡看汽車左右兩。