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[ DevCourseWeb com ] Udemy - Intelligently Extract Text and Data from Document with OCR NER
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1. Introduction
01_Pytesseract.ipynb
02_Data_Preparation.ipynb
03_Data_Preprocessing.ipynb
04_Predictions.ipynb
1. Introduction.mp4
1. Introduction.srt
2. Download the Resources.html
3. Facing any Issue with the Course Here is the solution.mp4
3. Facing any Issue with the Course Here is the solution.srt
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base_config.cfg
businessCard.csv
businessCard.txt
config.cfg
data
242.jpeg
54.jpg
6.jpg
TestData.pickle
TrainData.pickle
test.spacy
train.spacy
ipynb_checkpoints
01_Pytesseract-checkpoint.ipynb
02_Data_Preparation-checkpoint.ipynb
03_Data_Preprocessing-checkpoint.ipynb
04_Predictions-Copy1-checkpoint.ipynb
04_Predictions-checkpoint.ipynb
output
model-best
config.cfg
meta.json
ner
cfg
model
moves
tok2vec
cfg
model
tokenizer
vocab
key2row
lookups.bin
strings.json
vectors
model-last
config.cfg
meta.json
ner
cfg
model
moves
tok2vec
cfg
model
tokenizer
vocab
key2row
lookups.bin
strings.json
vectors
preprocess.py
2. Project Setup
1. Install Python.mp4
1. Install Python.srt
2. Install Virtual Environment.mp4
2. Install Virtual Environment.srt
3. Install Packages into Virtual Environment.mp4
3. Install Packages into Virtual Environment.srt
3.1 requirements.txt
4. Install Tesseract OCR & Pytesseract.mp4
4. Install Tesseract OCR & Pytesseract.srt
4.1 tesseract.txt
5. Install spaCy.mp4
5. Install spaCy.srt
5.1 spaCy.html
6. Test, the packages are installed.mp4
6. Test, the packages are installed.srt
3. Data Preparation
1. Project Plan.mp4
1. Project Plan.srt
1.1 1_Flow_diagram.pdf
10. Save data in csv.mp4
10. Save data in csv.srt
10.1 businessCard.csv
11. Labeling.mp4
11. Labeling.srt
2. Load Business Card using OpenCV & PIL.mp4
2. Load Business Card using OpenCV & PIL.srt
2.1 01_Pytesseract.ipynb
2.2 BusinessCardData.zip
3. Pytesseract Extract text from Image.mp4
3. Pytesseract Extract text from Image.srt
4. Pytesseract Tesseract Error.mp4
4. Pytesseract Tesseract Error.srt
5. Pytesseract How Pytesseract with work .mp4
5. Pytesseract How Pytesseract with work .srt
6. Pytesseract Image to text to dataframe.mp4
6. Pytesseract Image to text to dataframe.srt
7. Pytesseract Clean Text in Dataframe.mp4
7. Pytesseract Clean Text in Dataframe.srt
8. Pytesseract Draw Bounding Box around each word.mp4
8. Pytesseract Draw Bounding Box around each word.srt
9. Extract Text and Data from all Business Card.mp4
9. Extract Text and Data from all Business Card.srt
9.1 02_Data_Preparation.ipynb
4. Data Preprocessing and Cleaning
1. Spacy Training Data Format.mp4
1. Spacy Training Data Format.srt
2. Load Data and convert into Pandas DataFrame.mp4
2. Load Data and convert into Pandas DataFrame.srt
2.1 03_Data_Preprocessing.ipynb
2.2 businessCard.txt
3. Cleaning Text.mp4
3. Cleaning Text.srt
4. Convert Data into spacy format.mp4
4. Convert Data into spacy format.srt
5. Testing Entities.mp4
5. Testing Entities.srt
6. Convert data into spacy format for all Business card text.mp4
6. Convert data into spacy format for all Business card text.srt
7. Splitting Data into Training and Testing Set.mp4
7. Splitting Data into Training and Testing Set.srt
7.1 TestData.pickle
7.2 TrainData.pickle
5. Train Named Entity Recognition (NER) model
1. Spacy Fill the Configuration.mp4
1. Spacy Fill the Configuration.srt
1.1 base_config.cfg
1.2 config.cfg
2. Spacy Prepare Data.mp4
2. Spacy Prepare Data.srt
2.1 preprocess.py
2.2 test.spacy
2.3 train.spacy
3. Spacy Train NER pipeline model.mp4
3. Spacy Train NER pipeline model.srt
4. Spacy Save NER Model.mp4
4. Spacy Save NER Model.srt
output
model-best
config.cfg
meta.json
ner
cfg
model
moves
tok2vec
cfg
model
tokenizer
vocab
key2row
lookups.bin
strings.json
vectors
model-last
config.cfg
meta.json
ner
cfg
model
moves
tok2vec
cfg
model
tokenizer
vocab
key2row
lookups.bin
strings.json
vectors
6. Predictions
1. Import Required Libraries.mp4
1. Import Required Libraries.srt
1.1 04_Predictions.ipynb
1.2 6.jpg
10. Join token dataframe with Pytesseract data.mp4
10. Join token dataframe with Pytesseract data.srt
11. Bounding Box and Tagging Predicted Entities.mp4
11. Bounding Box and Tagging Predicted Entities.srt
12. Combine the BIO information.mp4
12. Combine the BIO information.srt
13. Bounding Box.mp4
13. Bounding Box.srt
14. Parsing Function.mp4
14. Parsing Function.srt
15. Testing.mp4
15. Testing.srt
16. Parse Entitles.mp4
16. Parse Entitles.srt
17. Predictions Function.mp4
17. Predictions Function.srt
18. Final Prediction Pipeline.mp4
18. Final Prediction Pipeline.srt
2. Clean Text Function.mp4
2. Clean Text Function.srt
3. Load Spacy NER Model.mp4
3. Load Spacy NER Model.srt
4. Extract Text from Image and Convert into Data Frame.mp4
4. Extract Text from Image and Convert into Data Frame.srt
5. Convert Data Frame into Content.mp4
5. Convert Data Frame into Content.srt
6. Get Named Entities from model.mp4
6. Get Named Entities from model.srt
7. Displacy render.mp4
7. Displacy render.srt
8. Tagging Each Word.mp4
8. Tagging Each Word.srt
9. Join Label to tokens dataframe.mp4
9. Join Label to tokens dataframe.srt
7. Improve Model Performance
1. Ideas to Improve model accuracy.mp4
1. Ideas to Improve model accuracy.srt
2. Version-2 model framework Data Preprocessing.mp4
2. Version-2 model framework Data Preprocessing.srt
3. Train Version 2 model.mp4
3. Train Version 2 model.srt
4. Get Predictions from the model.mp4
4. Get Predictions from the model.srt
8. Document Scanner
1. Download the Resources.html
10. Magic Color to Image.mp4
10. Magic Color to Image.srt
11. Integrate NER Predictions.mp4
11. Integrate NER Predictions.srt
2. What and Why Document Scanner in OpenCV .mp4
2. What and Why Document Scanner in OpenCV .srt
2_DocumentScanner
1_document_scanner.ipynb
__pycache__
predictions.cpython-39.pyc
images
001.jpg
015.jpg
03.jpg
033.jpg
ipynb_checkpoints
1_document_scanner-checkpoint.ipynb
output
model-best
config.cfg
meta.json
ner
cfg
model
moves
tok2vec
cfg
model
tokenizer
vocab
key2row
lookups.bin
strings.json
vectors
model-last
config.cfg
meta.json
ner
cfg
model
moves
tok2vec
cfg
model
tokenizer
vocab
key2row
lookups.bin
strings.json
vectors
predictions.py
3. Setup and Read Image.mp4
3. Setup and Read Image.srt
4. Resize Image with same aspect ratio.mp4
4. Resize Image with same aspect ratio.srt
5. Edge Detection (Enhance, Blur and Canny) to Document.mp4
5. Edge Detection (Enhance, Blur and Canny) to Document.srt
6. Dilate Edges with morphological transform.mp4
6. Dilate Edges with morphological transform.srt
7. Find Four Point Countours (Identify Location of document).mp4
7. Find Four Point Countours (Identify Location of document).srt
8. Apply Wrap transform and crop only document.mp4
8. Apply Wrap transform and crop only document.srt
9. Document Scanner Function Putting All together.mp4
9. Document Scanner Function Putting All together.srt
9. BONUS
1. Bonus Lecture Next Steps.html
Bonus Resources.txt
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