
CINIC-10 Image Classification Challenge
Classify the images in the dataset belonging to their respective categories.
Challenge
Welcome to CINIC-10 Image Classification Challenge
CINIC-10 is a drop-in replacement for CIFAR-10. It is compiled as a bench-marking dataset because CIFAR-10 can be too small/too easy and ImageNet is often too large/difficult. CINIC-10 fills this bench-marking gap. CINIC-10 has a total of 270,000 images equally split into three subsets: train, validate, and test. In each subset (90,000 images) there are ten classes (identical to CIFAR-10 classes). There are 9,000 images per class per subset.
Label Description
- airplane
- automobile
- bird
- cat
- deer
- dog
- frog
- horse
- ship
- truck
Citation
CINIC-10 is not ImageNet or CIFAR-10, https://arxiv.org/abs/1810.03505
The dateset includes 10 training directories with images corresponding to classes and 1 test directory.
The output has to be generated for the "test" directory having 90,000 images.
The final submission must include:
output.csv (single file having results for "test" directory which contains 90,000 images )
For grading, "output.csv" file must be uploaded in the submission section of this challenge.
The first row should correspond to the column names "filename" and "label".
Sample output.csv:
Please note:
- 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.
Judgement
- Accuracy Score
Rules
- The submission should be in a proper format as described by "Submission Guidelines".
- Late submission will not be accepted beyond provided deadline (Indian Standard Time).
NOTE: We may request for the code files if there is any discrepancy in your score. Your score will be marked invalid if the request for code is not fulfilled by you.
Reward
- Top three participants will get a place in Hall of Fame page.
Challenge Started