文件列表82
- 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
