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

Creation Time	Nov. 16, 2023, 8:38 a.m.
Last Access Time	Oct. 12, 2024, 9:40 a.m.
File Size	2.1 GB
Keywords	Plate 04 Web Python App Number Udemy 2021 in OCR Automatic Recognition
Total Requests	75
Total Files	82
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

1. Introduction/2.1 Project_Files.zip 473.4 MB
8. Number Plate Web App/6. Integrate Deep Learning Object Detection Model.mp4 141.7 MB
3. Data Processing/3. Data Preprocessing.mp4 83.4 MB
2. Labeling/5. XML to CSV.mp4 81.9 MB
8. Number Plate Web App/8. Display Output in HTML Page.mp4 78.2 MB
5. Pipeline Object Detection Model/1. Make Predictions.mp4 74.9 MB
8. Number Plate Web App/9. Display Output in HTML Page part 2.mp4 71.2 MB
6. Optical Character Recognition (OCR)/3. Exrtract Number Plate text from Image.mp4 67.4 MB
8. Number Plate Web App/7. Integrate Number Plate Detection and OCR to Flask App.mp4 66.9 MB
3. Data Processing/1. Read Data.mp4 61.1 MB
8. Number Plate Web App/5. HTTP Method Upload File in Flask.mp4 56.7 MB
5. Pipeline Object Detection Model/5. Create Pipeline.mp4 55.4 MB
3. Data Processing/2. Verify Labeled Data.mp4 48.6 MB
6. Optical Character Recognition (OCR)/1. Install Tesseract.mp4 47.8 MB
7. Flask App/3. Render HTML Template.mp4 47.6 MB
4. Deep Learning for Object Detection/2. InceptionResnet V2 model building.mp4 45.0 MB
2. Labeling/3. Install Dependencies.mp4 40.3 MB
5. Pipeline Object Detection Model/4. Bounding Box.mp4 39.1 MB
7. Flask App/1. Install Visual Studio Code.mp4 38.8 MB
7. Flask App/2. First Flask App.mp4 38.2 MB
2. Labeling/4. Label Images.mp4 32.1 MB
5. Pipeline Object Detection Model/3. De-normalize the Output.mp4 30.6 MB
5. Pipeline Object Detection Model/2. Make Predictions part2.mp4 30.0 MB
4. Deep Learning for Object Detection/8. Tensorboard.mp4 28.2 MB
3. Data Processing/4. Split train and test set.mp4 27.4 MB
8. Number Plate Web App/1. Create Web App.mp4 25.7 MB
7. Flask App/4. Import Boostrap.mp4 25.7 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 24.1 MB
4. Deep Learning for Object Detection/4. Compiling Model.mp4 23.9 MB
8. Number Plate Web App/4. Upload Form in HTML.mp4 22.8 MB
2. Labeling/2. Download Image Annotation Tool.mp4 22.8 MB
8. Number Plate Web App/3. Template Inheritance.mp4 22.2 MB
4. Deep Learning for Object Detection/5. InceptionResnet V2 Training.mp4 21.5 MB
2. Labeling/1. Get the Data.mp4 18.6 MB
4. Deep Learning for Object Detection/1. Get Transfer Learning from TensorFlow 2.x.mp4 17.4 MB
4. Deep Learning for Object Detection/3. Defining Inputs and Outputs.mp4 14.4 MB
6. Optical Character Recognition (OCR)/2. Install Pytesseract.mp4 13.0 MB
8. Number Plate Web App/2. Footer.mp4 12.8 MB
1. Introduction/1. Project Architecture.mp4 12.5 MB
2. Labeling/2.1 labelImg-master.zip 6.3 MB
8. Number Plate Web App/6. Integrate Deep Learning Object Detection Model.srt 15.3 KB
5. Pipeline Object Detection Model/1. Make Predictions.srt 10.8 KB
3. Data Processing/3. Data Preprocessing.srt 10.6 KB
8. Number Plate Web App/8. Display Output in HTML Page.srt 9.5 KB
8. Number Plate Web App/5. HTTP Method Upload File in Flask.srt 8.6 KB
3. Data Processing/1. Read Data.srt 8.2 KB
7. Flask App/3. Render HTML Template.srt 7.9 KB
8. Number Plate Web App/9. Display Output in HTML Page part 2.srt 7.4 KB
4. Deep Learning for Object Detection/2. InceptionResnet V2 model building.srt 7.2 KB
6. Optical Character Recognition (OCR)/3. Exrtract Number Plate text from Image.srt 7.1 KB
3. Data Processing/2. Verify Labeled Data.srt 6.7 KB
2. Labeling/5. XML to CSV.srt 6.6 KB
7. Flask App/2. First Flask App.srt 6.5 KB
8. Number Plate Web App/7. Integrate Number Plate Detection and OCR to Flask App.srt 6.1 KB
5. Pipeline Object Detection Model/5. Create Pipeline.srt 5.7 KB
5. Pipeline Object Detection Model/4. Bounding Box.srt 5.4 KB
6. Optical Character Recognition (OCR)/1. Install Tesseract.srt 5.0 KB
5. Pipeline Object Detection Model/2. Make Predictions part2.srt 4.9 KB
4. Deep Learning for Object Detection/8. Tensorboard.srt 4.8 KB
7. Flask App/1. Install Visual Studio Code.srt 4.6 KB
5. Pipeline Object Detection Model/3. De-normalize the Output.srt 4.1 KB
3. Data Processing/4. Split train and test set.srt 4.0 KB
8. Number Plate Web App/4. Upload Form in HTML.srt 3.8 KB
4. Deep Learning for Object Detection/5. InceptionResnet V2 Training.srt 3.8 KB
8. Number Plate Web App/1. Create Web App.srt 3.8 KB
1. Introduction/1. Project Architecture.srt 3.4 KB
8. Number Plate Web App/3. Template Inheritance.srt 3.3 KB
7. Flask App/4. Import Boostrap.srt 3.2 KB
4. Deep Learning for Object Detection/1. Get Transfer Learning from TensorFlow 2.x.srt 3.1 KB
4. Deep Learning for Object Detection/7. Save Deep Learning Model.srt 2.7 KB
4. Deep Learning for Object Detection/4. Compiling Model.srt 2.7 KB
4. Deep Learning for Object Detection/6. InceptionResnet V2 Training - Part 2.srt 2.7 KB
8. Number Plate Web App/2. Footer.srt 2.2 KB
2. Labeling/4. Label Images.srt 1.9 KB
6. Optical Character Recognition (OCR)/2. Install Pytesseract.srt 1.7 KB
4. Deep Learning for Object Detection/3. Defining Inputs and Outputs.srt 1.7 KB
2. Labeling/2. Download Image Annotation Tool.srt 1.7 KB
2. Labeling/1. Get the Data.srt 1.2 KB
2. Labeling/3. Install Dependencies.srt 1.2 KB
9. BONUS/1. Bonus Lecture.html 685 bytes
1. Introduction/2. Download the Resources.html 113 bytes

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

File List

Download Torrent

Related Resources

Copyright Infringement