Performance metrics show that YOLOv4 tiny is roughly 8X as fast at inference time as YOLOv4 and roughly 2/3 as performant on MS COCO (a very hard dataset). On small custom detection tasks that are more tractable, you will see even less of a performance degradation. On the custom example...
In any case, it's clear MT-YOLOv6 (hereafter YOLOv6 for brevity) is popular. In a couple short weeks, the repo has attracted over 2,000+ stars and 300+ forks. Let's dive in to how to train YOLOv6 on a custom dataset. The custom dataset we'll be using for this post isChess ...
train-yolos-huggingface-object-detection-on-custom-data.ipynb train-yolov10-object-detection-on-custom-dataset.ipynb train-yolov4-tiny-object-detection-on-custom-data.ipynb train-yolov5-classification-on-custom-data.ipynb train-yolov5-instance-segmentation-on-custom-data.ipynb train-yolov5-object-de...
1.Currently i am using tiny-yolo-voc.cfg which generates a model of size 63MB by using squeeze net would the model size decrease ?? 2.Or can u suggest any other .cfg file which i can use to reduce my model size Li-Lai commented Nov 22, 2017 question 1: I haven't test it. ...
Create a pretrained YOLO v3 deep learning network configured to retrain on the new dataset by using the yolov3ObjectDetector function. Get detector = yolov3ObjectDetector("tiny-yolov3-coco",classes,anchorBoxes); detector.Network ans = dlnetwork with properties: Layers: [44×1 nnet.cnn.layer....