https://github.com/Stick-To/Object-Detection-Tensorflow

centernet detection-api-tensorflow fcos image-augmentor lightheadrcnn object-detection pfpnet rcnn refinedet retinanet ssd tensorflow yolo

Last synced: 5 months ago
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Object Detection API Tensorflow

Host: GitHub
URL: https://github.com/Stick-To/Object-Detection-Tensorflow
Owner: Stick-To
License: mit
Created: 2019-05-16T13:02:45.000Z (almost 6 years ago)
Default Branch: master
Last Pushed: 2021-05-02T08:22:25.000Z (almost 4 years ago)
Last Synced: 2024-08-02T01:16:28.365Z (9 months ago)
Topics: centernet, detection-api-tensorflow, fcos, image-augmentor, lightheadrcnn, object-detection, pfpnet, rcnn, refinedet, retinanet, ssd, tensorflow, yolo
Language: Python
Homepage:
Size: 228 KB
Stars: 273
Watchers: 15
Forks: 92
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

awesome-yolo-object-detection - Stick-To/Object-Detection-Tensorflow - To/Object-Detection-Tensorflow?style=social"/> : Object Detection API Tensorflow. (Other Versions of YOLO)
awesome-yolo-object-detection - Stick-To/Object-Detection-Tensorflow - To/Object-Detection-Tensorflow?style=social"/> : Object Detection API Tensorflow. (Other Versions of YOLO)

README

# Object-Detection-API-Tensorflow

# Features
## Every model is implemented in only one file!
# Models

Yolo2

Yolo3

SSD

RetinaNet

RefineDet

Light Head Rcnn

PFPNet

CenterNet

FCOS

# Train your own data
# Train your own data
## 1. TFRecord generation

1) voc format dataset

2) fill in utils.voc_classname_encoder.py

3) run utils.test_voc_utils.py

## 2. config online image augmentor

fill in dict 'image_augmentor_config' in test-model.py

see utils.image_augmentor.py for details

see https://github.com/Stick-To/Online_Image_Augmentor_tensorflow for details
## 3. config model

fill in dict 'config' in test-model.py

## 4. Train
run test-model.py

The pre-trained vgg_16.ckpt could be downloaded from http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

## 5. Test
run annotated code in test-model.py

## 6. ImageNet pretraining
see utils.tfrecord_imagenet_utils.py

## 7. different conv backone
https://github.com/Stick-To/Deep_Conv_Backone

## 8. Instantiation of result
corresponding repository in https://github.com/Stick-To

# Experimental Environment
python3.7 tensorflow1.13