Could you help please with AlexeyAB / darknet

[Vladimir-v1]

Hello! First, thank you so much for your work and this solution! I'm trying to use TensorRT version of darknet on Jetson Xavier, instead of https://github.com/pjreddie/darknet, but getting NULL Pointer error. Could you please explain and give advice if it possible to resolve this issue

Thank you so much in advance!

root@jetsonNX:/home/user/Vehicle-Front-Rear-Detection-for-License-Plate-Detection-Enhancement# python Front_Rear_Detect.py FRD Net pre-loading... Try to load cfg: data/FRD/FRNet_YOLOv3_tiny.cfg, clear = 0 0 : compute_capability = 720, cudnn_half = 1, GPU: Xavier net.optimized_memory = 0 mini_batch = 1, batch = 1, time_steps = 1, train = 1 layer filters size/strd(dil) input output 0 Create CUDA-stream - 0 Create cudnn-handle 0 conv 16 3 x 3/ 1 416 x 416 x 3 -> 416 x 416 x 16 0.150 BF 1 max 2x 2/ 2 416 x 416 x 16 -> 208 x 208 x 16 0.003 BF 2 conv 32 3 x 3/ 1 208 x 208 x 16 -> 208 x 208 x 32 0.399 BF 3 max 2x 2/ 2 208 x 208 x 32 -> 104 x 104 x 32 0.001 BF 4 conv 64 3 x 3/ 1 104 x 104 x 32 -> 104 x 104 x 64 0.399 BF 5 max 2x 2/ 2 104 x 104 x 64 -> 52 x 52 x 64 0.001 BF 6 conv 128 3 x 3/ 1 52 x 52 x 64 -> 52 x 52 x 128 0.399 BF 7 max 2x 2/ 2 52 x 52 x 128 -> 26 x 26 x 128 0.000 BF 8 conv 256 3 x 3/ 1 26 x 26 x 128 -> 26 x 26 x 256 0.399 BF 9 max 2x 2/ 2 26 x 26 x 256 -> 13 x 13 x 256 0.000 BF 10 conv 512 3 x 3/ 1 13 x 13 x 256 -> 13 x 13 x 512 0.399 BF 11 max 2x 2/ 1 13 x 13 x 512 -> 13 x 13 x 512 0.000 BF 12 conv 1024 3 x 3/ 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BF 13 conv 256 1 x 1/ 1 13 x 13 x1024 -> 13 x 13 x 256 0.089 BF 14 conv 512 3 x 3/ 1 13 x 13 x 256 -> 13 x 13 x 512 0.399 BF 15 conv 21 1 x 1/ 1 13 x 13 x 512 -> 13 x 13 x 21 0.004 BF 16 yolo [yolo] params: iou loss: mse (2), iou_norm: 0.75, obj_norm: 1.00, cls_norm: 1.00, delta_norm: 1.00, scale_x_y: 1.00 17 route 13 -> 13 x 13 x 256 18 conv 128 1 x 1/ 1 13 x 13 x 256 -> 13 x 13 x 128 0.011 BF 19 upsample 2x 13 x 13 x 128 -> 26 x 26 x 128 20 route 19 8 -> 26 x 26 x 384 21 conv 256 3 x 3/ 1 26 x 26 x 384 -> 26 x 26 x 256 1.196 BF 22 conv 21 1 x 1/ 1 26 x 26 x 256 -> 26 x 26 x 21 0.007 BF 23 yolo [yolo] params: iou loss: mse (2), iou_norm: 0.75, obj_norm: 1.00, cls_norm: 1.00, delta_norm: 1.00, scale_x_y: 1.00 Total BFLOPS 5.449 avg_outputs = 325057 Allocate additional workspace_size = 38.79 MB Try to load weights: data/FRD/FRNet_YOLOv3_tiny_126000.weights Loading weights from data/FRD/FRNet_YOLOv3_tiny_126000.weights... seen 64, trained: 8064 K-images (126 Kilo-batches_64) Done! Loaded 24 layers from weights-file Loaded - names_list: data/FRD/FRNet.names, classes = 2 2021-06-17 22:57:35.861504 ('\t\t\tdetecting front and rear using FRD..., Model:', 'data/FRD/FRNet_YOLOv3_tiny.cfg') Traceback (most recent call last): File "Front_Rear_Detect.py", line 68, in FRs, cate = fr_detect(img, start) File "Front_Rear_Detect.py", line 32, in fr_detect results, wh = dn.detect(FR_net, FR_meta, img, threshold) File "/home/user/Vehicle-Front-Rear-Detection-for-License-Plate-Detection-Enhancement/darknet/python/darknet.py", line 160, in detect if dets[j].prob[i] > 0: ValueError: NULL pointer access