Giter Club home page Giter Club logo

license-plate-recognition's Introduction

Hi, I'm Manh. Here's a bit about myself

  • 👨🏻‍💻 I'm studying at Ha Noi University Of Science And Technology.
  • 🔭 I'm working at AI Research Team, R&D Unit, Sun* Inc as Machine Learning Engineer 🌱!
  • 💡 I love innovation and new technologies
  • 🥅 2020 Goals: Collect and share more knowledge with others. Please see my blog.
  • ⚡ Fun fact: I love gym and fishing

Connect with me:

Languages

Python C Java

Framework

  • 🗣 Tensorflow | Keras | Pytorch
  • 🖇️ OpenCV | Pillow
  • 🛢️ MySQL
  • :octocat: Git | Github
  • 🌐 Fast Api | BentoML | Docker

Computer Vision Project

Age, Gender, Smile Multitask Learning License Plate Recognition Automatic Scoring by OpenCV and Deep Learning EfficientNet Age, Gender Estimation

Natural Language Processing Project

Viet Nam Identity Card Recognition Vietnames Ocr Tool VietnameseOCRCorrection

license-plate-recognition's People

Contributors

buiquangmanhhp1999 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar

license-plate-recognition's Issues

Nhận dạng trên video

Bạn ơi cho mình hỏi thực hiện nhận dạng từ video thế nào ạ? Xin cám ơn bạn.

Inquiry About Dataset, Model Architecture, and Experimental Procedures

Dear buiquangmanhhp1999,
I hope this message finds you well. I have been exploring your fascinating project on License Plate Recognition and am impressed with its capabilities and design. However, I have a few questions regarding some specific aspects of your project, which I believe would greatly enhance my understanding and potentially contribute to its further development.

  1. Dataset Details:

    • Could you provide more information about the dataset used for training and testing the models, particularly Yolo Tiny v3 and the CNN for character classification?
    • Are there any specific preprocessing steps or augmentations applied to the dataset?
  2. Model Architecture:

    • Regarding the Yolo Tiny v3 model used for plate detection, could you share insights into any modifications or optimizations made to the standard architecture?
    • For the CNN used in character classification, I'm curious about the layer configurations, activation functions, and any unique features or techniques employed.
  3. Experimental Methods:

    • Could you elaborate on the training procedure, including details like loss functions, optimizers, learning rate schedules, and any regularization techniques used?
    • How do you handle the challenges of plate recognition in diverse conditions, such as varying angles, lighting, or partial occlusions?

I believe these details will not only clarify the workings of your project but also provide valuable insights for those looking to contribute or learn from your work.

Thank you for your time and effort in developing this project. I look forward to your response and any additional information you can provide.

Best regards,
yihong1120

lỗi OpenCV

image
Chào mọi người! t có tham khảo và chạy thử project của tác giả, nhưng gặp lỗi này. Ai đã từng gặp phải hay cách giải quyết có thể chỉ giúp mình được không? Cảm ơn mọi người.

Run

bạn ơi. Mình chạy nó báo lỗi path ở đoạn path='.data/categorized/digits/'
bạn xem giúp mình với

Chạy không được

Có cách nào sửa không bạn
2023-10-19 10:59:01.230960: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE SSE2 SSE3 SSE4.1 SSE4.2 AVX AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
File "D:\Bien_so_xe\License-Plate-Recognition\main.py", line 30, in
image = model.predict(img)
File "D:\Bien_so_xe\License-Plate-Recognition\src\lp_recognition.py", line 44, in predict
for coordinate in self.extractLP(): # detect license plate by yolov3
File "D:\Bien_so_xe\License-Plate-Recognition\src\lp_recognition.py", line 33, in extractLP
coordinates = self.detectLP.detect(self.image)
File "D:\Bien_so_xe\License-Plate-Recognition\src\lp_detection\detect.py", line 29, in detect
outputs = self.model.forward(utils.get_output_layers(self.model))
File "D:\Bien_so_xe\License-Plate-Recognition\src\data_utils.py", line 57, in get_output_layers
output_layers = [layers_name[i[0] - 1] for i in model.getUnconnectedOutLayers()]
File "D:\Bien_so_xe\License-Plate-Recognition\src\data_utils.py", line 57, in
output_layers = [layers_name[i[0] - 1] for i in model.getUnconnectedOutLayers()]
IndexError: invalid index to scalar variable.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.