How to Re-train custom yolo weights?

Question

I have done a custom detection in YOLOv3 over 3 classes, but the detections were not accurate so I want to retrain my custom YOLO weights with more images, but when I run it with new images it immediately finished, what is it that I have done wrong?

Here how I train it

 !./darknet detector train data/obj.data cfg/yolov3_custom.cfg yolov3_custom_last.weights

The content of obj.data:

classes = 3
train = data/train.txt
valid = data/test.txt
names = data/obj.names
backup = /mydrive/yolov3/backup/

The content of yolov3_custom.cfg:

# Training
batch=64
subdivisions=16
width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 6000
policy=steps
steps=4800,5400
scales=.1,.1

Answer 1

Simply change the path to the weights file in the command for training the model and run it again. There is no need to update the max_batches parameter or change the configuration file in any way. The framework is aware of how many iterations that a given set of weights has been trained for when retraining a model. For instance, if you are to stop after 2000 iterations in the initial training process, when retraining using the set of weights that was created as a result, it will begin at the 2001th iteration.