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

Creation Time	Nov. 16, 2023, 8:38 a.m.
Last Access Time	Nov. 20, 2024, 1:30 a.m.
File Size	2.1 GB
Keywords	Plate 04 Web Python App Number Udemy 2021 in OCR Automatic Recognition
Total Requests	76
Total Files	82
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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)

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