torchvision0.15.2+cu118 will affect cv2.imshow() in opencv4.7.0 does not respond

[goldwater668]

🐛 Describe the bug

import cv2 import torch from torchvision import transforms

img_path="1.jpg" cv_img = cv2.imread(img_path) print(cv_img.shape) cv2.imshow("winame", cv_img) cv2.waitKey(0)

Versions

torchvision0.15.2+cu118 will affect cv2.imshow() in opencv4.7.0 does not respond Images that need to display opencv must comment out torchvision But it has no effect in torchvision0.15.2

[pmeier]

Please run python -m torch.utils.collect_env and post the results here.

[goldwater668]

Collecting environment information... PyTorch version: 2.0.1+cu118 Is debug build: False CUDA used to build PyTorch: 11.8 ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 7.5.0-6ubuntu2) 7.5.0 Clang version: Could not collect CMake version: version 3.26.3 Libc version: glibc-2.31

Python version: 3.10.11 (main, Apr 20 2023, 19:02:41) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-5.15.0-73-generic-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 11.8.89 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3060 Nvidia driver version: 525.116.04 cuDNN version: Probably one of the following: /usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn.so.7 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 /usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 /usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian Address sizes: 39 bits physical, 48 bits virtual CPU(s): 20 On-line CPU(s) list: 0-19 Thread(s) per core: 1 Core(s) per socket: 12 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 151 Model name: 12th Gen Intel(R) Core(TM) i7-12700F Stepping: 2 CPU MHz: 2100.000 CPU max MHz: 4900.0000 CPU min MHz: 800.0000 BogoMIPS: 4224.00 Virtualization: VT-x L1d cache: 288 KiB L1i cache: 192 KiB L2 cache: 7.5 MiB NUMA node0 CPU(s): 0-19 Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l2 invpcid_single cdp_l2 ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdt_a rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr flush_l1d arch_capabilities

Versions of relevant libraries: [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.24.3 [pip3] pytorch-lightning==2.0.2 [pip3] torch==2.0.1+cu118 [pip3] torchaudio==2.0.2+cu118 [pip3] torchmetrics==0.11.4 [pip3] torchvision==0.15.2+cu118 [conda] numpy 1.24.3 pypi_0 pypi [conda] pytorch-lightning 2.0.2 pypi_0 pypi [conda] torch 2.0.1+cu118 pypi_0 pypi [conda] torchaudio 2.0.2+cu118 pypi_0 pypi [conda] torchmetrics 0.11.4 pypi_0 pypi [conda] torchvision 0.15.2+cu118 pypi_0 pypi @pmeier

[CristoJV]

I can confirm the issue; it occurs for me as well with torchvision==0.16.0+cu118 and opencv_python==4.9.0. I had to downgrade OpenCV to version 4.5.0 to resolve the problem.

@pmeier

import cv2
import torchvision
if __name__ == "__main__":
    frame = cv2.imread("/app/tests/res/smiling_face.png")
    # Display the image
    cv2.imshow("Smiling face", frame)
    # Wait for a key press
    cv2.waitKey(0)