Hello,
I try to switch my YoloV4 detection model from color to Grayscale.
Predictions resulkt from Tao training are ok :
Start to calculate AP for each class
cargo AP 0.64015
fishing AP 0.65369
kayak AP 0.51335
passenger AP 0.73766
pleasurecraft AP 0.83856
sailing AP 0.675
tanker AP 0.68877
mAP 0.67817
My Pipeline is Basic :
gst-launch-1.0 filesrc location=/home/tao/Videos/Montage.mp4 ! qtdemux ! h264parse ! nvv4l2decoder ! m.sink_0 nvstreammux name=m batch-size=1 width=1920 height=1080 ! nvinfer config-file-path=/home/tao/Documents/Svn/DeepTrack/Configurations/Boat/Day/V7/InferenceBoat.txt ! nvvideoconvert ! nvdsosd ! nveglglessink
My InferenceBoat.txt file :
[property]
gpu-id=0
net-scale-factor=1.0
offsets=30048.9216
model-color-format=2
labelfile-path=labels.txt
model-engine-file=yolov4_resnet18_epoch_080.onnx_b1_gpu0_fp32.engine
tlt-encoded-model=yolov4_resnet18_epoch_080.onnx
tlt-model-key=nvidia_tlt
infer-dims=1;1024;1344
maintain-aspect-ratio=0
uff-input-order=0
uff-input-blob-name=Input
batch-size=1
0=FP32, 1=INT8, 2=FP16 mode
network-mode=0
num-detected-classes=7
interval=0
gie-unique-id=1
is-classifier=1
#network-type=0
Set to NMS
cluster-mode=3
output-blob-names=BatchedNMS
parse-bbox-func-name=NvDsInferParseCustomBatchedNMSTLT
custom-lib-path=libnvds_infercustomparser.so
[class-attrs-all]
pre-cluster-threshold=0.3
roi-top-offset=0
roi-bottom-offset=0
detected-min-w=8
detected-min-h=4
detected-max-w=2400
detected-max-h=1800
is set model-color-format to 2.
I assume nvfiner do the conversion to Grayscale 16 bits before inference (is in documentation).
infer-dims is ok model was training with 1344*1024 as size.
But nothing is detected when i run inference on video ?
Where i can find example configuration file for yolov4 16bit grayscale ?