pyav 14.0.0 breaks write_video

[raphaelschwinger]

🐛 Describe the bug

import torch
import torchvision

# Example dummy video tensor
video = torch.randint(0, 255, (30, 720, 1280, 3), dtype=torch.uint8)  # 30 frames of 720p video

# Write the video
torchvision.io.write_video("test_video.mp4", video, fps=30, video_codec="h264")

Outputs:

File av/video/frame.pyx:193, in av.video.frame.VideoFrame.pict_type.__set__()

TypeError: an integer is required

Versions

Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 11.7.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A100 80GB PCIe
GPU 1: NVIDIA A100 80GB PCIe
GPU 2: NVIDIA A100 80GB PCIe
GPU 3: NVIDIA A100 80GB PCIe

Nvidia driver version: 550.120
cuDNN version: Could not collect
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
Address sizes:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               32
On-line CPU(s) list:                  0-31
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 72F3 8-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   2
Core(s) per socket:                   8
Socket(s):                            2
Stepping:                             1
Frequency boost:                      enabled
CPU max MHz:                          4137.2070
CPU min MHz:                          1500.0000
BogoMIPS:                             7399.76
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca
Virtualization:                       AMD-V
L1d cache:                            512 KiB (16 instances)
L1i cache:                            512 KiB (16 instances)
L2 cache:                             8 MiB (16 instances)
L3 cache:                             512 MiB (16 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-7,16-23
NUMA node1 CPU(s):                    8-15,24-31
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Mitigation; safe RET
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; Retpolines; IBPB conditional; IBRS_FW; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==2.1.3
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pytorch-lightning==2.4.0
[pip3] torch==2.5.1
[pip3] torchmetrics==1.6.0
[pip3] torchrl==0.6.0
[pip3] torchvision==0.20.1
[pip3] triton==3.1.0
[conda] Could not collect

python = "^3.10"
torch = "^2.5.1"
torchvision = "^0.20.1"
lightning = "^2.4.0"
torchmetrics = "^1.5.1"
hydra-core = "^1.3.2"
hydra-colorlog = "^1.2.0"
hydra-optuna-sweeper = "^1.2.0"
rootutils = "^1.0.7"
pre-commit = "^4.0.1"
rich = "^13.9.4"
pytest = "^8.3.3"
torchrl = "^0.6.0"
tensordict = "^0.6.2"
ipykernel = "^6.29.5"
gymnasium = {extras = ["atari"], version = "<1.0.0"}
pygame = "^2.6.1"
av = "^14.0.0"

ffmpeg version 4.4.2-0ubuntu0.22.04.1

Downgrading to 13.1.0 solves the problem.

[raphaelschwinger]

See PyAV-Org/PyAV#1666

[NicolasHug]

Thanks for the report @raphaelschwinger .

Indeed pyav made some backward-incompatible changes with pyav 14. I have made the necessary changes to torchvision in #8776, and they will be available with the next release. Until then, users will need to pin pyav to < 14 for it to work.

[raphaelschwinger]

@NicolasHug Thanks!

[refill-dn]

I have same case.
I was fix torchvision/io/video.py

[hiyyg]

Is there any update on how to fix this issue more elegantly?

[refill]

I think this issue was already patched.

see vision/torchvision/io/video.py line 160

...
for img in video_array:
frame = av.VideoFrame.from_ndarray(img, format="rgb24")
try:
frame.pict_type = "NONE"
except TypeError:
from av.video.frame import PictureType # noqa

            frame.pict_type = PictureType.NONE

...