FGVC | Fine-Grained Visual Classification for Plants & Flowers | Machine Learning library

 by   lucasxlu Python Version: Current License: MIT

kandi X-RAY | FGVC Summary

kandi X-RAY | FGVC Summary

FGVC is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. FGVC has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However FGVC build file is not available. You can download it from GitHub.

Train ResNet to recognize over 998 categories (997 plants + 1 others) for Kaggle Competition. Deep Learning for Plants Disease Recognition for AI Challenger 2018 Competition.
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              FGVC has a low active ecosystem.
              It has 13 star(s) with 6 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 1 have been closed. On average issues are closed in 12 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of FGVC is current.

            kandi-Quality Quality

              FGVC has 0 bugs and 0 code smells.

            kandi-Security Security

              FGVC has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              FGVC code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              FGVC is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              FGVC releases are not available. You will need to build from source code and install.
              FGVC has no build file. You will be need to create the build yourself to build the component from source.
              FGVC saves you 729 person hours of effort in developing the same functionality from scratch.
              It has 1682 lines of code, 59 functions and 30 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed FGVC and discovered the below as its top functions. This is intended to give you an instant insight into FGVC implemented functionality, and help decide if they suit your requirements.
            • Run plant type validation
            • Train a model using FFT
            • Forward transform function
            • Computes the phi of the phi
            • Copy files from_target to to to_target_dir
            • Creates a directory if it does not exist
            • Infer predictions from an image file
            • Load data
            • Infer from an image
            • Infer from input image
            • Run FashionMNIST
            • Concatenates an image using BIDS
            • Convert CSV file to JSON format
            • Get access token
            • Runs a resnet
            • Evaluate model inference
            • Train a model
            Get all kandi verified functions for this library.

            FGVC Key Features

            No Key Features are available at this moment for FGVC.

            FGVC Examples and Code Snippets

            No Code Snippets are available at this moment for FGVC.

            Community Discussions

            QUESTION

            Why does Anaconda install pytorch cpuonly when I install cuda?
            Asked 2022-Mar-23 at 20:46

            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:

            ...

            ANSWER

            Answered 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 torch.cuda.is_available().

            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!

            Now torch.cuda.is_available() evaluates to True

            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

            Source https://stackoverflow.com/questions/71162459

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install FGVC

            You can download it from GitHub.
            You can use FGVC like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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          • HTTPS

            https://github.com/lucasxlu/FGVC.git

          • CLI

            gh repo clone lucasxlu/FGVC

          • sshUrl

            git@github.com:lucasxlu/FGVC.git

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