kandi X-RAY | FGVC Summary
kandi X-RAY | FGVC Summary
[ECCV 2020] Flow-edge Guided Video Completion
Top functions reviewed by kandi - BETA
- Calculate flowNN gradient
- Get the flowNN of the image .
- Calculate video completion .
- Train the model .
- Runs the flow completion .
- Updates the metrics .
- Solve Poisson polynomial problem .
- Calculate flow .
- Calculates the gradient of the flow source frame .
- Constructs an equation for an equation .
FGVC Key Features
FGVC Examples and Code Snippets
# Stage 1: training with CUB dataset python3.6 pretrain_cub.py --dataset cub --exp_name pretrain_cub --gpu_id 0 --config ./config/pretrain_cub.json # Stage 2: training with Birds-to-Words and NABirds dataset alternately python3.6 pretrain.py --da
import sys sys.path.append('/path/to/projectroot/') from fast_bird_part_localization import settings sys.path.append(settings.CAFFE_PYTHON_PATH) import caffe from fast_bird_part_localization import detector fbp = detector('/path/to/project/models/he
train_dataset = Cub2011('./cub2011', train=True, download=False) test_dataset = Cub2011('./cub2011', train=False, download=False)
Trending Discussions on FGVC
I have created a Python 3.7 conda virtual environment and installed the following packages using this command:
conda install pytorch torchvision torchaudio cudatoolkit=11.3 matplotlib scipy opencv -c pytorch
They install fine, but then when I come to run my program I get the following error which suggests that a CUDA enabled device is not found:...
ANSWERAnswered 2022-Feb-18 at 14:52
I beleive I had the following things wrong that prevented me from using Cuda. Despite having cuda installed the
nvcc --version command indicated that Cuda was not installed and so what I did was add it to the path using this answer.
Despite doing that and deleting my original conda environment and using the
conda install pytorch torchvision torchaudio cudatoolkit=11.3 matplotlib scipy opencv -c pytorch command again I still got
False when evaluating
I then used this command
conda install pytorch torchvision torchaudio cudatoolkit=10.2 matplotlib scipy opencv -c pytorch changing cudatoolkit from verison 11.3 to version 10.2 and then it worked!
torch.cuda.is_available() evaluates to
Unfortunately, Cuda version 10.2 was incompatible with my RTX 3060 gpu (and I'm assuming it is not compatible with all RTX 3000 cards). Cuda version 11.0 was giving me errors and Cuda version 11.3 only installs the CPU only versions for some reason. Cuda version 11.1 worked perfectly though!
This is the command I used to get it to work in the end:
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
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