Is there anyone who can confirm this to work?
One of my tests on a space on HuggingFace runs for 35000 seconds already, trying to make a 50s video. It does NOT need proportionally 10 minutes for every 5 seconds of video. Ten minutes are 600 seconds, so it would need 6000 seconds. It's not finished after more than 30k.The devs and maintainers should test their own software.
We are trying to improve the inference performance.
For now, 50 seconds video is too long for one inference. Suggested reasoning using 5 to 15 second videos. You can cut your video first.
Thank you :)
Thanks. I found out the image needs to be cut down to 256x256. I didn't see this anywhere mentioned in the space. I will try again for 50s, but with a low resolution.
I would also appreciate if it was somewhere mentioned if I could profit from renting some more permanent space. This might especially matter if a space is running for a long time, and then going into sleep mode because I set a timeout. Is the result stored in some folder?
===== Application Startup at 2024-07-31 00:58:27 =====
The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling transformers.utils.move_cache().
0it [00:00, ?it/s]
0it [00:00, ?it/s]
INFO:httpx:HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 "
INFO:httpx:HTTP Request: GET https://api.gradio.app/pkg-version "HTTP/1.1 200 OK"
Running on local URL: http://0.0.0.0:7860
INFO:httpx:HTTP Request: GET http://localhost:7860/startup-events "HTTP/1.1 200 OK"
INFO:httpx:HTTP Request: HEAD http://localhost:7860/ "HTTP/1.1 200 OK"
To create a public link, set share=True in launch().
WARNING:py.warnings:/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:69: UserWarning: Specified provider 'CUDAExecutionProvider' is not in available provider names.Available providers: 'AzureExecutionProvider, CPUExecutionProvider'
warnings.warn(
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/1k3d68.onnx landmark_3d_68 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/2d106det.onnx landmark_2d_106 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/genderage.onnx genderage ['None', 3, 96, 96] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/glintr100.onnx recognition ['None', 3, 112, 112] 127.5 127.5
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/scrfd_10g_bnkps.onnx detection [1, 3, '?', '?'] 127.5 128.0
set det-size: (640, 640)
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/queueing.py", line 532, in process_events
response = await route_utils.call_process_api(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/route_utils.py", line 276, in call_process_api
output = await app.get_blocks().process_api(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/blocks.py", line 1928, in process_api
result = await self.call_function(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/blocks.py", line 1514, in call_function
prediction = await anyio.to_thread.run_sync(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/anyio/to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 2177, in run_sync_in_worker_thread
return await future
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 859, in run
result = context.run(func, *args)
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/utils.py", line 832, in wrapper
response = f(*args, **kwargs)
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/utils.py", line 832, in wrapper
response = f(*args, **kwargs)
File "/home/user/app/app.py", line 33, in run_inference
inference_process(args)
File "/home/user/app/scripts/inference.py", line 162, in inference_process
source_image_lip_mask = image_processor.preprocess(
File "/home/user/app/hallo/datasets/image_processor.py", line 124, in preprocess
face = sorted(faces, key=lambda x: (x["bbox"][2] - x["bbox"][0]) * (x["bbox"][3] - x["bbox"][1]))[-1]
IndexError: list index out of range
WARNING:py.warnings:/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:69: UserWarning: Specified provider 'CUDAExecutionProvider' is not in available provider names.Available providers: 'AzureExecutionProvider, CPUExecutionProvider'
warnings.warn(
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/1k3d68.onnx landmark_3d_68 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/2d106det.onnx landmark_2d_106 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/genderage.onnx genderage ['None', 3, 96, 96] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/glintr100.onnx recognition ['None', 3, 112, 112] 127.5 127.5
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ./pretrained_models/face_analysis/models/scrfd_10g_bnkps.onnx detection [1, 3, '?', '?'] 127.5 128.0
set det-size: (640, 640)
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/queueing.py", line 532, in process_events
response = await route_utils.call_process_api(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/route_utils.py", line 276, in call_process_api
output = await app.get_blocks().process_api(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/blocks.py", line 1928, in process_api
result = await self.call_function(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/blocks.py", line 1514, in call_function
prediction = await anyio.to_thread.run_sync(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/anyio/to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 2177, in run_sync_in_worker_thread
return await future
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 859, in run
result = context.run(func, *args)
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/utils.py", line 832, in wrapper
response = f(*args, **kwargs)
File "/home/user/.pyenv/versions/3.10.14/lib/python3.10/site-packages/gradio/utils.py", line 832, in wrapper
response = f(*args, **kwargs)
File "/home/user/app/app.py", line 33, in run_inference
inference_process(args)
File "/home/user/app/scripts/inference.py", line 162, in inference_process
source_image_lip_mask = image_processor.preprocess(
File "/home/user/app/hallo/datasets/image_processor.py", line 124, in preprocess
face = sorted(faces, key=lambda x: (x["bbox"][2] - x["bbox"][0]) * (x["bbox"][3] - x["bbox"][1]))[-1]
IndexError: list index out of range
Same here.
I stopped trying, since I could now sign up with Hedra AI. It wasn't possible before outside of the US. It can make one minute videos and I like it. Of course, I would still be happy if there was something open and I would test it.