I compute the class_weight and retrain my experiment, but the result still not good. I try to increase L1 weight_decay, but the map will become 0.
Is detectnet_v2 not good for unbalanced data or close bboxes in images?
for i in range(len(class_count_array)):
class_weight_array[i]= 1.0 / (class_count_array[i] / max_class_count)
I use yolov3 of TLT and get better result about map(92.0).
I use yolov3 detector(word detector) as secondary inference engine in deepstream. When the one special plate is close to image boundary, my word detector will crash.
0:06:05.745221257 5732 0x17aa8280 WARN nvinfer gstnvinfer.cpp:1240:convert_batch_and_push_to_input_thread:<secondary_gie_0> error: NvBufSurfTransform failed with error -2 while converting buffer
ERROR from secondary_gie_0: NvBufSurfTransform failed with error -2 while converting buffer
Debug info: /dvs/git/dirty/git-master_linux/deepstream/sdk/src/gst-plugins/gst-nvinfer/gstnvinfer.cpp(1240): convert_batch_and_push_to_input_thread (): /GstPipeline:pipeline/GstBin:secondary_gie_bin/GstNvInfer:secondary_gie_0