[Udemy] Automatic Number Plate Recognition, OCR Web App in Python (04.2021)

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文件数目：82个文件
文件大小：2.06 GB
收录时间：2021-12-27
访问次数：6
相关内容：Udemy Automatic Number Plate Recognition Python 2021

文件meta

1. Introduction/2.1 Project_Files.zip
473.38 MB
8. Number Plate Web App/6. Integrate Deep Learning Object Detection Model.mp4
141.72 MB
3. Data Processing/3. Data Preprocessing.mp4
83.36 MB
2. Labeling/5. XML to CSV.mp4
81.86 MB
8. Number Plate Web App/8. Display Output in HTML Page.mp4
78.17 MB
5. Pipeline Object Detection Model/1. Make Predictions.mp4
74.93 MB
8. Number Plate Web App/9. Display Output in HTML Page part 2.mp4
71.25 MB
6. Optical Character Recognition (OCR)/3. Exrtract Number Plate text from Image.mp4
67.37 MB
8. Number Plate Web App/7. Integrate Number Plate Detection and OCR to Flask App.mp4
66.89 MB
3. Data Processing/1. Read Data.mp4
61.14 MB
8. Number Plate Web App/5. HTTP Method Upload File in Flask.mp4
56.66 MB
5. Pipeline Object Detection Model/5. Create Pipeline.mp4
55.4 MB
3. Data Processing/2. Verify Labeled Data.mp4
48.62 MB
6. Optical Character Recognition (OCR)/1. Install Tesseract.mp4
47.8 MB
7. Flask App/3. Render HTML Template.mp4
47.65 MB
4. Deep Learning for Object Detection/2. InceptionResnet V2 model building.mp4
45 MB
2. Labeling/3. Install Dependencies.mp4
40.33 MB
5. Pipeline Object Detection Model/4. Bounding Box.mp4
39.08 MB
7. Flask App/1. Install Visual Studio Code.mp4
38.79 MB
7. Flask App/2. First Flask App.mp4
38.2 MB
2. Labeling/4. Label Images.mp4
32.08 MB
5. Pipeline Object Detection Model/3. De-normalize the Output.mp4
30.59 MB
5. Pipeline Object Detection Model/2. Make Predictions part2.mp4
30.03 MB
4. Deep Learning for Object Detection/8. Tensorboard.mp4
28.23 MB
3. Data Processing/4. Split train and test set.mp4
27.4 MB
8. Number Plate Web App/1. Create Web App.mp4
25.71 MB
7. Flask App/4. Import Boostrap.mp4
25.69 MB
4. Deep Learning for Object Detection/6. InceptionResnet V2 Training - Part 2.mp4
24.6 MB
4. Deep Learning for Object Detection/7. Save Deep Learning Model.mp4
24.07 MB
4. Deep Learning for Object Detection/4. Compiling Model.mp4
23.94 MB
8. Number Plate Web App/4. Upload Form in HTML.mp4
22.79 MB
2. Labeling/2. Download Image Annotation Tool.mp4
22.78 MB
8. Number Plate Web App/3. Template Inheritance.mp4
22.21 MB
4. Deep Learning for Object Detection/5. InceptionResnet V2 Training.mp4
21.48 MB
2. Labeling/1. Get the Data.mp4
18.58 MB
4. Deep Learning for Object Detection/1. Get Transfer Learning from TensorFlow 2.x.mp4
17.43 MB
4. Deep Learning for Object Detection/3. Defining Inputs and Outputs.mp4
14.45 MB
6. Optical Character Recognition (OCR)/2. Install Pytesseract.mp4
12.98 MB
8. Number Plate Web App/2. Footer.mp4
12.76 MB
1. Introduction/1. Project Architecture.mp4
12.49 MB
2. Labeling/2.1 labelImg-master.zip
6.28 MB
8. Number Plate Web App/6. Integrate Deep Learning Object Detection Model.srt
15.33 KB
5. Pipeline Object Detection Model/1. Make Predictions.srt
10.81 KB
3. Data Processing/3. Data Preprocessing.srt
10.61 KB
8. Number Plate Web App/8. Display Output in HTML Page.srt
9.46 KB
8. Number Plate Web App/5. HTTP Method Upload File in Flask.srt
8.55 KB
3. Data Processing/1. Read Data.srt
8.16 KB
7. Flask App/3. Render HTML Template.srt
7.94 KB
8. Number Plate Web App/9. Display Output in HTML Page part 2.srt
7.35 KB
4. Deep Learning for Object Detection/2. InceptionResnet V2 model building.srt
7.2 KB