Gradio app works for the example images, fails for any other image(s)

[SoftologyPro]

Running the gradio app locally on Windows under it's own virtual enviroment.
It starts fine and the examples work.
When I select another image (example attached) I get this error...

Traceback (most recent call last):
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\gradio\queueing.py", line 489, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\gradio\blocks.py", line 1179, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\anyio\_backends\_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\gradio\utils.py", line 678, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\LucidDreamer\luciddreamer.py", line 170, in run
    gaussians = self.create(
  File "D:\Tests\LucidDreamer\luciddreamer.py", line 187, in create
    self.traindata = self.generate_pcd(rgb_cond, txt_cond, neg_txt_cond, pcdgenpath, seed, diff_steps)
  File "D:\Tests\LucidDreamer\luciddreamer.py", line 352, in generate_pcd
    depth_curr = self.d(image_curr)
  File "D:\Tests\LucidDreamer\luciddreamer.py", line 157, in d
    return self.d_model.infer_pil(im)
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\depth_model.py", line 141, in infer_pil
    out_tensor = self.infer(x, pad_input=pad_input, with_flip_aug=with_flip_aug, **kwargs)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\depth_model.py", line 126, in infer
    return self.infer_with_flip_aug(x, pad_input=pad_input, **kwargs)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\depth_model.py", line 110, in infer_with_flip_aug
    out = self._infer_with_pad_aug(x, pad_input=pad_input, **kwargs)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\depth_model.py", line 88, in _infer_with_pad_aug
    out = self._infer(x)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\depth_model.py", line 55, in _infer
    return self(x)['metric_depth']
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\zoedepth\zoedepth_v1.py", line 144, in forward
    rel_depth, out = self.core(x, denorm=denorm, return_rel_depth=True)
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\base_models\midas.py", line 262, in forward
    x = self.prep(x)
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\base_models\midas.py", line 186, in __call__
    return self.normalization(self.resizer(x))
  File "D:\Tests\LucidDreamer\./ZoeDepth\zoedepth\models\base_models\midas.py", line 173, in __call__
    return nn.functional.interpolate(x, (height, width), mode='bilinear', align_corners=True)
  File "D:\Tests\LucidDreamer\voc_luciddreamer\lib\site-packages\torch\nn\functional.py", line 3924, in interpolate
    raise TypeError(
TypeError: expected size to be one of int or Tuple[int] or Tuple[int, int] or Tuple[int, int, int], but got size with types [<class 'numpy.int32'>, <class 'numpy.int32'>]

[Oclysh]

Perhaps you can convert the format of 'height' and 'width' to int in a function of 'n.function.interpolate'.

[Haimzis]

@SoftologyPro
Could you please share your environment? I also tried running their examples but only received noisy outputs.