Automatic Number Plate Recognition, OCR Web App in Python
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Intermediate
2 Students -
3 hours, 2 minutes
Automatic Number Plate Recognition, OCR Web App in Python
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Overview
It’s time you raise your standard high in the field of data science. Understand how to construct an OCR Web app in Python for ANPR with this highly acclaimed Automatic Number Plate Recognition, OCR Web App in Python course .
ANPR helps in tracking good and bad vehicles as well as providing vital information for spotting criminals. The purpose of this super exclusive Automatic Number Plate Recognition OCR Web App in Python course is to teach you how to build an OCR Web app in Python for automatic number plate recognition from the bottom up. The training includes modelling techniques such as object detection model, data pre preprocessing and model evaluation. It will enhance your Image processing and object detection skills which are required of data scientists.
Enrol now and learn how to develop web app projects with Python.
Course design
The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.
You are taught through a combination of
- Video lessons
- Online study materials
Will I receive a certificate of completion?
Upon successful completion, you will qualify for the UK and internationally-recognised CPD accredited certification. You can choose to make your achievement formal by obtaining your PDF Certificate at the cost of £9 and Hard Copy Certificate for £15.
Why study this course
It doesn’t matter if you are an aspiring professional or absolute beginner; this course will enhance your expertise and boost your CV with critical skills and an accredited certification attesting to your knowledge.
The Automatic Number Plate Recognition, OCR Web App in Python is fully available to anyone, and no previous qualifications are needed to enrol. All One Education needs to know is that you are eager to learn and are over 16.
Course Curriculum
| Module 01: What we will do | |||
| Project Architecture | 00:03:00 | ||
| Module 02: Date and Labeling | |||
| Get the data | 00:01:00 | ||
| Download annotation | 00:02:00 | ||
| Requirements annotation | 00:03:00 | ||
| Labeling | 00:02:00 | ||
| XML to CSV | 00:10:00 | ||
| Read data | 00:08:00 | ||
| Verify data | 00:06:00 | ||
| Module 03: Preprocessing | |||
| Data preprocessing | 00:10:00 | ||
| Split data into train test | 00:03:00 | ||
| Module 04: Train Object Detection Model | |||
| Model building part 1 | 00:03:00 | ||
| Model building part 2 | 00:06:00 | ||
| Model building part 3 | 00:02:00 | ||
| Model building part 4 | 00:02:00 | ||
| Model Training new | 00:04:00 | ||
| Train again | 00:02:00 | ||
| Save model | 00:03:00 | ||
| Tensorboard | 00:04:00 | ||
| Module 05: Pipeline | |||
| Test model | 00:10:00 | ||
| Test model part 2 | 00:04:00 | ||
| Denormalize | 00:04:00 | ||
| Bounding | 00:05:00 | ||
| Make Pipeline | 00:05:00 | ||
| Module 06: OCR | |||
| Install tesseract OCR | 00:05:00 | ||
| Install pytesseract | 00:02:00 | ||
| OCR numberplate | 00:06:00 | ||
| Module 07: 7 Number Plate Web App | |||
| Install VS code | 00:04:00 | ||
| First flask | 00:07:00 | ||
| Render template | 00:07:00 | ||
| Boostrap | 00:03:00 | ||
| Navbar | 00:03:00 | ||
| Footer | 00:02:00 | ||
| Template inheritance | 00:03:00 | ||
| Upload | 00:04:00 | ||
| Integrate deeplearning | 00:13:00 | ||
| Integrate | 00:06:00 | ||
| Get output part 1 | 00:08:00 | ||
| Get output part 2 | 00:07:00 | ||
| Assignment | |||
| Assignment – Automatic Number Plate Recognition, OCR Web App in Python | 00:00:00 | ||
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