Bigthinx Sketch Classification Challenge
The aim of the challenge is to classify sketches in unstructured environments.
Welcome to Bigthinx Sketch Classification Challenge!
Bigthinx is hiring a full time data scientist via this AI challenge. All you need to do is to make a submission to be eligible for an interview. For this position Bigthinx is looking for an individual with an experience of upto 1 years.
In this challenge you are required to create an AI model that classifies sketch into 220 classes. Inside the train folder we have 220 classes and each class has around 40 to 45 images. All the images are in grayscale format. Inside the test folder we have 1760 images on which you have make predictions.
Note: This is an invite only challenge and you will be able to participate if you have been invited by the organisation.
The final submission must include:
- output.csv (single file having results for "TEST" directory which contains 1760 images). The first row should correspond to the column names "Image Files" and "Labels".
- iPython Notebook to be submitted in the "My Submission Section".
How to make a submission?
- Click on "My Submission"
- On the next page, click on "+ New Submission"
- Upload your CSV in the next page and click on "Submit for Review"
- You must submit your CSV file by uploading the CSV in the "My Submissions" section of this challenge.
- Your submission will be auto graded and you will be able to see your results instantly.
- If there is any error in the submission, your final score will be marked as 0 or a warning prompt of “Invalid Score” will be displayed.
- You are allowed to use pretrained networks as part of your solution. Here we ask you to specify the pretraining strategy (dataset and general training parameters) in the description field of your submission.
- You are allowed to use supplementary training images from external datasets. In recent years a few datasets in a similar domain have been released. Here we also ask you to specify the training procedure in the description field of your submission.
- You are allowed to use ensemble techniques as part of your solution.
- You can add additional annotation information to the training and validation data, but we then want the extended dataset to be made publicly available for all competitors.
- We are using an automatic anti-cheat system. Our system flags submission which has low trust scores. Manually modifying your submission CSV (via comparison of any form etc.), using image comparison techniques (pixel matching, file size matching, etc,), in any form, can lead to your disqualification without any notice.
- Submission must not include copyrighted code. If the violation is found, the submission will be rejected.
- The submission should be in a proper format as described by "Submission Guidelines".
- Late submission will not be accepted beyond the provided deadline (Indian Standard Time).
NOTE: We may request the code files if there is any discrepancy in your score. Your score will be marked invalid or you can be disqualified if the request for code is not fulfilled by you.
- Eligibility for an interview for Full-time hiring.
- The participants with a successful submission will get a certificate of participation.
- The top 3 participants will receive a permanent place in Dockship's "Hall of Fame".