No tensor arguments when running Batch Image Detection on own photos

[JaimyvS]

First of all, thanks for building the MegaDetector and keeping it free to use for everyone.

In the past, I've successfully used the previous version of the MegaDetector but decided to install the new PyTorch Wildlife package.

I've tested the demo python scripts which all seem to work, but when I try to run the pw_data.DetectionImageFolder function on a folder of custom photos I get the following error:

Traceback (most recent call last): File "batch_giraf_detect.py", line 23, in results = detection_model.batch_image_detection(loader) File "/home/jaimy/CameraTraps/PytorchWildlife/models/detection/yolov5/base_detector.py", line 150, in batch_image_detection for pred in torch.cat(total_preds, dim=0).cpu() NotImplementedError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors, or that you (the operator writer) forgot to register a fallback function. Available functions are [CPU, CUDA, QuantizedCPU, BackendSelect, Python, Named, Conjugate, Negative, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradLazy, AutogradXPU, AutogradMLC, AutogradHPU, AutogradNestedTensor, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, UNKNOWN_TENSOR_TYPE_ID, Autocast, Batched, VmapMode].

CPU: registered at aten/src/ATen/RegisterCPU.cpp:18433 [kernel] CUDA: registered at aten/src/ATen/RegisterCUDA.cpp:26496 [kernel] QuantizedCPU: registered at aten/src/ATen/RegisterQuantizedCPU.cpp:1068 [kernel] BackendSelect: fallthrough registered at ../aten/src/ATen/core/BackendSelectFallbackKernel.cpp:3 [backend fallback] Python: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:47 [backend fallback] Named: registered at ../aten/src/ATen/core/NamedRegistrations.cpp:7 [backend fallback] Conjugate: registered at ../aten/src/ATen/ConjugateFallback.cpp:18 [backend fallback] Negative: registered at ../aten/src/ATen/native/NegateFallback.cpp:18 [backend fallback] ADInplaceOrView: fallthrough registered at ../aten/src/ATen/core/VariableFallbackKernel.cpp:64 [backend fallback] AutogradOther: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradCPU: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradCUDA: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradXLA: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradLazy: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradXPU: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradMLC: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradHPU: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradNestedTensor: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradPrivateUse1: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradPrivateUse2: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] AutogradPrivateUse3: registered at ../torch/csrc/autograd/generated/VariableType_3.cpp:10141 [autograd kernel] Tracer: registered at ../torch/csrc/autograd/generated/TraceType_3.cpp:11560 [kernel] UNKNOWN_TENSOR_TYPE_ID: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:466 [backend fallback] Autocast: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:305 [backend fallback] Batched: registered at ../aten/src/ATen/BatchingRegistrations.cpp:1016 [backend fallback] VmapMode: fallthrough registered at ../aten/src/ATen/VmapModeRegistrations.cpp:33 [backend fallback]

When I use the single image detect code as shown in the ReadTheDocs on a custom photo, it runs properly. Although in the output photo with bounding box, the colors seem to be altered a bit.

My photos are JPG's around 3 MB's in size each and a resolution of 6048 x 4024.

I've already tried to use the CPU instead of the GPU and lower the resolution of the images. But since a single image detect does work, this would probably not be the issue.

Any help would be much appreciated!