See BirdCLEF 2021 - Birdcall Identification Kaggle competition.
Install dependencies:
$ pip install -e '.[dev]'On Linux, you also need to run sudo apt-get install libsndfile1.
Install also TensorFlow if not installed in your environment:
$ pip install -e .[tf]$ dvc pullCreate smaller dataset in data/ folder:
$ python -m src.sample$ python -m src.download$ python -m src.train --model smoke-test --data-dir data --metadata-csv train_metadata_small.csvInstall kernel:
$ python -m ipykernel install --user --name bird-3.8.1 --display-name "Python (bird-3.8.1)"- Overview of BirdCLEF 2021
- Where to start: A collection of resources
- Best working note awards
- EfficientNet explained
- LifeCLEF2022
- freefield1010 dataset
- Birdcall Identification Using CNN and Gradient Boosting Decision Trees with Weak and Noisy Supervision
- Winning solution of BirdCLEF2021
- Bird audio detection challenge
- mixup: Beyond Empirical Risk Minimization
- SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
- TensorFlow IO Audio
- Simple Audio Recognition with TensorFlow
Create a GCP VM with at least 100 GB disk space. Give write access to Google Storage API.
SSH to the instance using:
$ gcloud compute ssh INSTANCE_NAMEInstall pip, tmux and unzip:
$ sudo apt install python3-pip tmux unzipInstall Kaggle CLI:
$ pip3 install kaggleMake directory .kaggle and transfer kaggle.json from your machine:
$ scp ~/.kaggle/kaggle.json USERNAME@VM_IP:~/.kaggle/kaggle.jsonCreate new tmux session:
$ tmux new -s kimmoDownload data to folder data/:
$ chmod 600 ~/.kaggle/kaggle.json
$ ./.local/bin/kaggle competitions download birdclef-2021 -p dataDetach from the session with Ctrl+b d and attach with tmux a -t kimmo.
Extract and copy data to Google bucket bird-clef-kimmo:
$ unzip data/birdclef-2021.zip -d data
$ gsutil -m rsync -r data gs://bird-clef-kimmo/dataList and stop instances:
$ gcloud compute instances list
$ gcloud compute instances stop INSTANCE_NAMECreate a user-managed notebook in Vertex AI Workbench.
SSH to the instance with jupyter username:
$ gcloud compute ssh jupyter@bird-exploreSetup SSH configuration:
$ gcloud compute config-sshSwitch User in ~/.ssh/config:
# ~/.ssh/config
Host some-host
User jupyter
Connecting from VS Code using the SSH host should now use jupyter as user, allowing you to use /home/jupyter for files and save remotely.
You can also setup port forwarding to localhost with:
$ gcloud compute ssh jupyter@bird-explore -- -N -L 8080:localhost:8080Sign in to Kaggle. Follow the instructions to prepare ~/.kaggle/kaggle.json file.
See the Data page.
Download the full 39 GiB dataset:
$ kaggle competitions download birdclef-2021 -p dataDownload single file:
$ kaggle competitions download birdclef-2021 -p data/train_short_audio/acafly -f train_short_audio/acafly/XC109605.oggList all files in CSV format
$ kaggle competitions files birdclef-2021 --csvDownload train_metadata.csv:
$ kaggle competitions download birdclef-2021 -p data -f train_metadata.csv
$ unzip data/train_metadata.csv.zip -d data
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