yolov4 0.11.0

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tensorflow-yolov4

python3 -m pip install yolov4

YOLOv4 Implemented in Tensorflow 2.

Download yolov4.weights file: https://drive.google.com/open?id=1cewMfusmPjYWbrnuJRuKhPMwRe_b9PaT

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

Performance

Help

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

Inference

tensorflow

from yolov4.tf import YOLOv4

yolo = YOLOv4()

yolo.classes = "/home/hhk7734/tensorflow-yolov4/data/classes/coco.names"

yolo.make_model()
yolo.load_weights("/home/hhk7734/Desktop/yolov4.weights", weights_type="yolo")

yolo.inference(
    media_path="/home/hhk7734/tensorflow-yolov4/data/kite.jpg",
)

tensorflow lite

import yolov4.tflite as yolo

detector = yolo.YOLOv4(
    names_path="/home/hhk7734/tensorflow-yolov4/data/classes/coco.names",
    tflite_path="/home/hhk7734/Desktop/yolov4.tflite",
)

detector.inference(
    media_path="/home/hhk7734/tensorflow-yolov4/data/road.mp4",
    is_image=False,
    cv_waitKey_delay=1,
)

Training

from yolov4.tf import YOLOv4

yolo = YOLOv4()

yolo.classes = "/home/hhk7734/tensorflow-yolov4/data/classes/coco.names"

yolo.input_size = 416
yolo.make_model()
yolo.load_weights("/home/hhk7734/Desktop/yolov4.conv.137", weights_type="yolo")

datasets = yolo.load_datasets("/home/hhk7734/tensorflow-yolov4/data/dataset/val2017.txt")

yolo.compile(learning_rate=4e-7)
yolo.fit(datasets, epochs=4000, batch_size=4)

yolo.model.save_weights("checkpoints")

from yolov4.tf import YOLOv4

yolo = YOLOv4()

yolo.classes = "/home/hhk7734/tensorflow-yolov4/data/classes/coco.names"

yolo.input_size = 416
yolo.make_model()
yolo.load_weights("/home/hhk7734/Desktop/yolov4.conv.137", weights_type="yolo")

datasets = yolo.load_datasets(
    "/home/hhk7734/darknet/data/train.txt",
    datasets_type="yolo",
)

yolo.compile(learning_rate=4e-7)
yolo.fit(datasets, epochs=4000, batch_size=4)

yolo.model.save_weights("checkpoints")

tensorflow-yolov4 (0.11.0) unstable; urgency=medium

• tf: remove utils.draw_bbox in predict()
• yolov4: rename files and functions and change order
• utility: utils: remove get_anchors()
• utility: media: impelment resize(), draw_bbox()
• utility: utils: implement DIoU_NMS
• utility: utils: fix dimensional calculation problems
• utility: refactor dataset
• tf: remove train
• utility: train: implement make_compiled_loss()
• utility: media: fix bug that could not resize some images
• utility: train: remove problem of division by zero

-- Hyeonki Hong [e-mail] Mon, 29 Jun 2020 21:05:39 +0900

tensorflow-yolov4 (0.10.0) unstable; urgency=medium

• core: yolov4: refactor decode()
• core: utils: remove sigmoid in postprocess_bbboxe()
• tf: apply YOLOv4 changes to make_model()
• core: yolov4: move decode_train() to tf.YOLOv4.train()

-- Hyeonki Hong [e-mail] Thu, 25 Jun 2020 00:48:44 +0900

tensorflow-yolov4 (0.9.0) unstable; urgency=medium

• tf: modify hyperparameters as properties
• tf: add weights_type argument to load_weights()
• core: utils: implement _np_fromfile()
• core: utils: implement a way to partially load weights
• tf: train: move learning_rate_* to argument
• core: move YOLOConv2D to common
• core: common: remove bn argument of YOLOConv2D
• core: utils: refactor yolo_conv2d_set_weights
• core: yolov4: refactor YOLOv4
• core: utils: refactor load_weights
• tf: refactor make_model
• yolov4: change YoloV4 to YOLOv4

-- Hyeonki Hong [e-mail] Wed, 24 Jun 2020 02:58:27 +0900

tensorflow-yolov4 (0.8.0) unstable; urgency=medium

• core: use tf.keras.layers.UpSampling2D
• core: refactor Mish
• core: common: remove residual_block
• core: remove sequential in _ResBlock
• core: backbone: Set LeakyReLU's alpha to 0.1

-- Hyeonki Hong [e-mail] Tue, 23 Jun 2020 02:21:01 +0900

tensorflow-yolov4 (0.7.0) unstable; urgency=medium

• tf: fix to proceed to the next step even if an error occurs
• tf: modify video_interval_ms to cv_waitKey_delay
• core: backbone: refactor CSPDarknet53
• core: utils: implement csp_darknet53_set_weights()

-- Hyeonki Hong [e-mail] Mon, 22 Jun 2020 23:01:32 +0900

tensorflow-yolov4 (0.6.0) unstable; urgency=medium

• tf: set first_step_epochs according to the weight usage
• tf: fix syntax error

-- Hyeonki Hong [e-mail] Fri, 19 Jun 2020 17:09:57 +0900

tensorflow-yolov4 (0.5.0) unstable; urgency=medium

• core: dataset: add yolo type
• tf: add dataset_type parameter to YoloV4.train
• tf: add epochs parameter to train
• tf: add save_interval parameter to train

-- Hyeonki Hong [e-mail] Fri, 19 Jun 2020 14:30:50 +0900

tensorflow-yolov4 (0.4.0) unstable; urgency=medium

• core: dataset: remove cfg module
• tf: implement YoloV4.train

-- Hyeonki Hong [e-mail] Thu, 11 Jun 2020 17:45:44 +0900

tensorflow-yolov4 (0.3.0) unstable; urgency=medium

• core: utils: use numpy instead of tensorflow
• pypi: remove install_requires and change to manual installation
• yolov4: add video_interval_ms

-- Hyeonki Hong [e-mail] Mon, 08 Jun 2020 23:59:41 +0900

tensorflow-yolov4 (0.2.0) unstable; urgency=medium

• pylint: create .pylintrc and run black
• core: remove config.py
• yolov4: change tfyolov4 to yolov4
• yolov4: remove detect**.py and implement YoloV4.inference

-- Hyeonki Hong [e-mail] Mon, 08 Jun 2020 02:20:49 +0900

tensorflow-yolov4 (0.1.0) unstable; urgency=medium

• yolov4: fork from 'hunglc007/tensorflow-yolov4-tflite'

-- Hyeonki Hong [e-mail] Fri, 05 Jun 2020 20:17:45 +0900