OpenCV CUDA Backend Detection and Runtime Device Availability

Answer

Confirmed: cv::cuda::getCudaEnabledDeviceCount() returns the number of GPUs for which the CUDA runtime can create a context and whose compute capability is covered by the binaries compiled into OpenCV’s CUDA modules.

Runtime conditions that can yield zero

Confirmed fact: a zero result means OpenCV’s CUDA runtime initialization did not find a usable device.

Likely explanations, not verified without build/runtime data for this deployment:

• OpenCV built without CUDA support. A build with WITH_CUDA=OFF makes the function return zero regardless of hardware.
• Missing or mismatched CUDA runtime libraries at runtime, e.g., libcuda.so / libcudart.so absent or incompatible with the toolkit used to build OpenCV, preventing runtime initialization.
• GPU compute capability lower than the minimum architecture baked into the OpenCV CUDA kernels, so the device is ignored.
• Device visibility reduced to zero by CUDA_VISIBLE_DEVICES or access restrictions.

Analyzing deployment logs

Confirmed: symbol resolution failures are observable in logs.

Likely pattern: undefined symbol errors referencing cuda* symbols suggest missing or mismatched CUDA libraries at load time.

Likely pattern: logs showing device count zero without symbol errors, while nvidia-smi reports a GPU present, points toward a non-CUDA build, compute-capability mismatch, or device hiding.

Uncertainty: log wording varies by loader and packaging; definitive classification requires the actual log lines from this deployment.

Verifying CUDA integration

Confirmed: verification must combine build information with runtime checks.

Likely minimal checks for this case:

• Confirm the deployed OpenCV build reports CUDA enabled and the toolkit version used at build time.
• Confirm the OpenCV shared objects link against CUDA runtime libraries.
• Confirm driver visibility of the GPU and whether device hiding is in effect.

One missing diagnostic detail that changes the recommendation: the OpenCV build string or CMakeCache values for WITH_CUDA and CUDA_ARCH_BIN for the deployed binary. Without that, it is uncertain whether zero is due to a non-CUDA build versus a runtime mismatch.