Open goncz opened 4 years ago
You said:
....different width and height of the YOLO network
And your cfg file shows:
width=160 height=160
That looks very very small, in my opinion way way too small.
So which other width & height's have you tested, all in nearly the same area of 160 ? I would suggest to train at least with minimum width & height of 416 and if this doesn't work try once again with width & height of 608. If thats not working too, than i guess the problem is somewhere else
If you have an issue with training - no-detections / Nan avg-loss / low accuracy:
-show_imgs
i.e. ./darknet detector train ... -show_imgs
and look at the aug_...jpg
images, do you see correct truth bounded boxes?bad.list
and bad_label.list
if they existHow to train (to detect your custom objects)
and How to improve object detection
in the Readme: https://github.com/AlexeyAB/darknet/blob/master/README.md./darknet detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights data/dog.jpg
CUDA-version: 10000 (10000), cuDNN: 7.4.2, CUDNN_HALF=1, GPU count: 1
CUDNN_HALF=1
OpenCV version: 4.2.0
0 : compute_capability = 750, cudnn_half = 1, GPU: GeForce RTX 2070
net.optimized_memory = 0
mini_batch = 1, batch = 8, time_steps = 1, train = 0
layer filters size/strd(dil) input output
You must train 6000 iterations
I am trying to train a custom yolov3 model to detect a single class. My dataset consists of 450 training images and 50 validation images. The images have a resolution of 500x374, and the objects range from 100x40 to 250x250 pixels. The loss result when training is shown below where the loss converges pretty fast - most likely because of the small dataset.
However, when I test the produced weights
./darknet detector demo data/obj.data yolo-obj.cfg backup/yolo-obj_last.weights data/test.jpg
the iamge shows no detections. I've tested on several images, all with no detecitons.I've tried different learning rates (0.001, 0.0001, 0.0005), different width and height of the YOLO network, different
max_batches
.-show_imgs
flag shows correct augmentation of images with correct bounding boxes.Is my dataset too sparse? Something wrong with my cfg file? A side note is that mAP is not showing on the graph even though
-map
flag is enabled.Cloud
obj.data
yolo-obj.cfg