Mask Prediction

[ Getting Started Notebook ] Mask Recognition

A getting started notebook for the challenge.


Getting Started with Mask Recognition Challenge

In this puzzle, we have detect mask type and bounding box of the mask from the image of human face.

This is a starter kit explaining how to download the data and also submit direcly via this notebook.

We will be submitting the sample prediction directly in the required format.

AIcrowd code utilities for downloading data for Language Classification

Download the files 💾¶

Download AIcrowd CLI

We will first install aicrowd-cli which will help you download and later make submission directly via the notebook.

In [ ]:
!pip install aicrowd-cli
%load_ext aicrowd.magic
Collecting aicrowd-cli
  Downloading aicrowd_cli-0.1.10-py3-none-any.whl (44 kB)
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Requirement already satisfied: tqdm<5,>=4.56.0 in /usr/local/lib/python3.7/dist-packages (from aicrowd-cli) (4.62.3)
Collecting rich<11,>=10.0.0
  Downloading rich-10.16.2-py3-none-any.whl (214 kB)
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Collecting pyzmq==22.1.0
  Downloading pyzmq-22.1.0-cp37-cp37m-manylinux1_x86_64.whl (1.1 MB)
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Collecting requests-toolbelt<1,>=0.9.1
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Collecting requests<3,>=2.25.1
  Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)
     |████████████████████████████████| 63 kB 1.5 MB/s 
Collecting GitPython==3.1.18
  Downloading GitPython-3.1.18-py3-none-any.whl (170 kB)
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Requirement already satisfied: toml<1,>=0.10.2 in /usr/local/lib/python3.7/dist-packages (from aicrowd-cli) (0.10.2)
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Requirement already satisfied: typing-extensions>= in /usr/local/lib/python3.7/dist-packages (from GitPython==3.1.18->aicrowd-cli) (
Collecting gitdb<5,>=4.0.1
  Downloading gitdb-4.0.9-py3-none-any.whl (63 kB)
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Collecting smmap<6,>=3.0.1
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Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.25.1->aicrowd-cli) (2021.10.8)
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Collecting colorama<0.5.0,>=0.4.0
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Collecting commonmark<0.10.0,>=0.9.0
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Installing collected packages: smmap, requests, gitdb, commonmark, colorama, rich, requests-toolbelt, pyzmq, GitPython, aicrowd-cli
  Attempting uninstall: requests
    Found existing installation: requests 2.23.0
    Uninstalling requests-2.23.0:
      Successfully uninstalled requests-2.23.0
  Attempting uninstall: pyzmq
    Found existing installation: pyzmq 22.3.0
    Uninstalling pyzmq-22.3.0:
      Successfully uninstalled pyzmq-22.3.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.
datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.
Successfully installed GitPython-3.1.18 aicrowd-cli-0.1.10 colorama-0.4.4 commonmark-0.9.1 gitdb-4.0.9 pyzmq-22.1.0 requests-2.27.1 requests-toolbelt-0.9.1 rich-10.16.2 smmap-5.0.0

Login to AIcrowd ㊗¶

In [ ]:
%aicrowd login
Please login here: https://api.aicrowd.com/auth/60cuodJchV7xYp8XqtPb5kLEZjHvDYbuzIFuteLjHC0
API Key valid
Saved API Key successfully!

Download Dataset¶

We will create a folder name data and download the files there.

In [ ]:
!rm -rf data
!mkdir data
%aicrowd ds dl -c mask-prediction -o data
In [ ]:
!unzip data/train.zip -d data/train > /dev/null
!unzip data/val.zip -d data/val > /dev/null
!unzip data/test.zip -d data/test > /dev/null

Diving in the dataset 🕵️‍♂️

In [ ]:
import pandas as pd
import numpy as np
import os

Diving in the dataset 🕵️‍♂️

In [ ]:
train_images = 'data/train'
val_images = 'data/val'
test_images = 'data/test'

Generating Prediction File

In this starter kit we will directly be submitting the sample prediction file. In case you would like to see a submission via baseline model, check it out here.

In [ ]:
submission = pd.read_csv('data/sample_submission.csv')
In [ ]:
Out[ ]:
ImageID bbox masktype
0 seed6252 (0,0,1,1) cloth
1 seed4684 (0,0,1,1) cloth
2 seed1731 (0,0,1,1) cloth
3 seed4742 (0,0,1,1) cloth
4 seed4521 (0,0,1,1) cloth
In [ ]:
!rm -rf assets
!mkdir assets
submission.to_csv(os.path.join("assets", "submission.csv"))

Submitting our Predictions

Note : Please save the notebook before submitting it (Ctrl + S)

In [ ]:
%aicrowd notebook submit -c mask-prediction -a assets --no-verify
Using notebook: Getting Starter Notebook for Mask Recognition Challenge for submission...
Removing existing files from submission directory...
Scrubbing API keys from the notebook...
Collecting notebook...

Submission Upload Error: Couldn't decode response from AIcrowd servers


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