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TensorFlow 2 YOLOv4


license pypi language

tensorflow-yolov4​

python3 -m pip install yolov4

YOLOv4 Implemented in Tensorflow 2.

Download Weights​

Dependencies​

python3 -m pip install opencv-python
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​

import cv2

from yolov4.tf import YOLOv4

yolo = YOLOv4()

yolo.config.parse_names("coco.names")
yolo.config.parse_cfg("yolov4-tiny.cfg")

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

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

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

yolo.inference(
    "/dev/video0",
    is_image=False,
    cv_apiPreference=cv2.CAP_V4L2,
    cv_frame_size=(640, 480),
    cv_fourcc="YUYV",
)

tensorflow lite​

from yolov4.tf import YOLOv4, save_as_tflite

yolo = YOLOv4()

yolo.config.parse_names("coco.names")
yolo.config.parse_cfg("yolov4-tiny.cfg")

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

save_as_tflite(
    model=yolo.model,
    tflite_path="yolov4-tiny-float16.tflite",
    quantization="float16",
)
from yolov4.tflite import YOLOv4

yolo = YOLOv4()

yolo.config.parse_names("coco.names")
yolo.config.parse_cfg("yolov4-tiny.cfg")

yolo.load_tflite("yolov4-tiny-float16.tflite")

yolo.inference("kite.jpg")