tensorflow-yolov4

python3 -m pip install yolov4

YOLOv4 Implemented in Tensorflow 2.

Download Weights

• yolov4-tiny.conv.29
• yolov4-tiny.weights
• yolov4-tiny-relu.weigths(incomplete)
• yolov4.conv.137
• yolov4.weights
• coco.names

Dependencies

python3 -m pip install -U pip setuptools wheel

python3 -m pip install numpy

Install OpenCV (cv2)

Tensorflow 2

python3 -m pip install tensorflow

TFlite

Ref: https://www.tensorflow.org/lite/guide/python

Objective

• Train and predict using TensorFlow 2 only
• Run yolov4-tiny-relu on Coral board(TPU).
• Train tiny-relu with coco 2017 dataset
• Update Docs
• Optimize model and operations

Performance

Help

>>> from yolov4.tf import YOLOv4
>>> help(YOLOv4)

Inference

tensorflow

from yolov4.tf import YOLOv4

yolo = YOLOv4()

yolo.classes = "coco.names"

yolo.make_model()
yolo.load_weights("yolov4.weights", weights_type="yolo")

yolo.inference(media_path="kite.jpg")

yolo.inference(media_path="road.mp4", is_image=False)

Object detection test jupyter notebook

from yolov4.tf import YOLOv4

yolo = YOLOv4(tiny=True)

yolo.classes = "coco.names"

yolo.make_model()
yolo.load_weights("yolov4-tiny.weights", weights_type="yolo")

yolo.inference(media_path="kite.jpg")

yolo.inference(media_path="road.mp4", is_image=False)

tensorflow lite

from yolov4.tf import YOLOv4

yolo = YOLOv4()

yolo.classes = "coco.names"

yolo.make_model()
yolo.load_weights("yolov4.weights", weights_type="yolo")

yolo.save_as_tflite("yolov4.tflite")

from yolov4.tflite import YOLOv4

yolo = YOLOv4()

yolo.classes = "coco.names"

yolo.load_tflite("yolov4.tflite")

yolo.inference("kite.jpg")

Training

https://wiki.loliot.net/docs/etc/project/yolov4/yolov4-training