TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.
Due to the different environment, I created a new project on VS2015 in windows10, and added your and tensorRT code to the project, the program was compiled and passed
When I tried to load a trained model based on yolov4-tiny, there was a memory out-of-bounds problem in line 1211 of trt_utils.cpp, and I tried to use yolov4-tiny and its pre-trained model yolov4-tiny.conv.29, the same problem occurred. All prompt errors in the 11th convolutional layer
https://github.com/enazoe/yolo-tensorrt/blob/322a1310adf28fb911f1e10415aa5de6432126aa/modules/trt_utils.cpp#L1211
File does not exist : D:/Code/yolo-tensorrt/configs/yolov4-tiny-kHALF-batch1.engine
Loading pre-trained weights...
Invalid network type
Loading complete!
layer inp_size out_size weightPtr
(1) conv-bn-leaky 3 x 416 x 416 32 x 208 x 208 992
(2) conv-bn-leaky 32 x 208 x 208 64 x 104 x 104 19680
(3) conv-bn-leaky 64 x 104 x 104 64 x 104 x 104 56800
(4) chunk 64 x 104 x 104 32 x 104 x 104 56800
(5) conv-bn-leaky 32 x 104 x 104 32 x 104 x 104 66144
(6) conv-bn-leaky 32 x 104 x 104 32 x 104 x 104 75488
(7) route - 64 x 104 x 104 75488
(8) conv-bn-leaky 64 x 104 x 104 64 x 104 x 104 79840
(9) route - 128 x 104 x 104 79840
(10) maxpool 128 x 104 x 104 128 x 52 x 52 79840
Due to the different environment, I created a new project on VS2015 in windows10, and added your and tensorRT code to the project, the program was compiled and passed When I tried to load a trained model based on yolov4-tiny, there was a memory out-of-bounds problem in line 1211 of trt_utils.cpp, and I tried to use yolov4-tiny and its pre-trained model yolov4-tiny.conv.29, the same problem occurred. All prompt errors in the 11th convolutional layer https://github.com/enazoe/yolo-tensorrt/blob/322a1310adf28fb911f1e10415aa5de6432126aa/modules/trt_utils.cpp#L1211 File does not exist : D:/Code/yolo-tensorrt/configs/yolov4-tiny-kHALF-batch1.engine Loading pre-trained weights... Invalid network type Loading complete! layer inp_size out_size weightPtr (1) conv-bn-leaky 3 x 416 x 416 32 x 208 x 208 992 (2) conv-bn-leaky 32 x 208 x 208 64 x 104 x 104 19680 (3) conv-bn-leaky 64 x 104 x 104 64 x 104 x 104 56800 (4) chunk 64 x 104 x 104 32 x 104 x 104 56800 (5) conv-bn-leaky 32 x 104 x 104 32 x 104 x 104 66144 (6) conv-bn-leaky 32 x 104 x 104 32 x 104 x 104 75488 (7) route - 64 x 104 x 104 75488 (8) conv-bn-leaky 64 x 104 x 104 64 x 104 x 104 79840 (9) route - 128 x 104 x 104 79840 (10) maxpool 128 x 104 x 104 128 x 52 x 52 79840