Face De-Blurring

[ Getting Started Notebook ] Face De-Blurring

Getting Started with Face Deblurring Challenge

In this puzzle, we have to de blur the blurred images.

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 [1]:

!pip install aicrowd-cli
%load_ext aicrowd.magic

Collecting aicrowd-cli
  Downloading aicrowd_cli-0.1.12-py3-none-any.whl (48 kB)
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Collecting rich<11,>=10.0.0
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Requirement already satisfied: python-slugify<6,>=5.0.0 in /usr/local/lib/python3.7/dist-packages (from aicrowd-cli) (5.0.2)
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  Downloading pyzmq-22.1.0-cp37-cp37m-manylinux1_x86_64.whl (1.1 MB)
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Collecting requests<3,>=2.25.1
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Collecting commonmark<0.10.0,>=0.9.0
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Collecting colorama<0.5.0,>=0.4.0
  Downloading colorama-0.4.4-py2.py3-none-any.whl (16 kB)
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-0.1.12 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

In [2]:

%aicrowd login

Please login here: https://api.aicrowd.com/auth/4hYw89LWS99FvIfan3Sv23267Ig5jUhe5FCingVv1yo
API Key valid
Gitlab access token valid
Saved details successfully!

Download Dataset¶¶

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

In [3]:

!rm -rf data
!mkdir data
%aicrowd ds dl -c face-de-blurring -o data

In [4]:

!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

Importing Libraries:¶

In [5]:

import pandas as pd
import numpy as np
import os

Diving in the dataset 🕵️‍♂️¶

In [6]:

train_blur_images = 'data/train/blur'
train_original_images = 'data/train/original'
val_blur_images = 'data/train/blur'
val_original_images = 'data/val/original'

Generating Prediction File¶

In this starter kit we will directly be submitting the blurred images. In case you would like to see a submission via baseline model.

In [7]:

!mkdir original
!cp -r data/test/blur/* original/

Submitting our Predictions¶

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

In [9]:

%aicrowd notebook submit -c face-de-blurring -a original   --no-verify

Using notebook: [Getting Started Notebook] Face De-Blur for submission...
Removing existing files from submission directory...
Scrubbing API keys from the notebook...
Collecting notebook...

                                                   ╭─────────────────────────╮                                                   
                                                   │ Successfully submitted! │                                                   
                                                   ╰─────────────────────────╯

                                                         Important links                                                         
┌──────────────────┬────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│  This submission │ https://www.aicrowd.com/challenges/ai-blitz-xiii/problems/face-de-blurring/submissions/172686              │
│                  │                                                                                                            │
│  All submissions │ https://www.aicrowd.com/challenges/ai-blitz-xiii/problems/face-de-blurring/submissions?my_submissions=true │
│                  │                                                                                                            │
│      Leaderboard │ https://www.aicrowd.com/challenges/ai-blitz-xiii/problems/face-de-blurring/leaderboards                    │
│                  │                                                                                                            │
│ Discussion forum │ https://discourse.aicrowd.com/c/ai-blitz-xiii                                                              │
│                  │                                                                                                            │
│   Challenge page │ https://www.aicrowd.com/challenges/ai-blitz-xiii/problems/face-de-blurring                                 │
└──────────────────┴────────────────────────────────────────────────────────────────────────────────────────────────────────────┘

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diego26dav

Almost 3 years ago

Hi @ashivani, I tried to run the code in Sagemaker Studio Lab and I get this error when I run “%aicrowd ds dl -c face-de-blurring -o data”:

AttributeError: ‘tqdm’ object has no attribute ‘disp’ Exception ignored in: <function tqdm.del at 0x7fdcd271dfc0> Traceback (most recent call last): File “/home/studio-lab-user/.conda/envs/aicrowd/lib/python3.10/site-packages/tqdm/std.py”, line 1147, in del “"”Backward-compatibility to use: for x in tqdm(iterable)””” File “/home/studio-lab-user/.conda/envs/aicrowd/lib/python3.10/site-packages/tqdm/notebook.py”, line 286, in close

No problems when running in Google Colab. But maybe you know why I got this error in Sagemaker? Best.

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