Result

Instructions

For training the model, use only the training set. Do not use validation and test sets.

The organizers request the team to upload the final/updated trained model, inference code, ReadMe file, and algorithm details on the competition website on or before 15th May 2024. If there is a mismatch between the results uploaded, the trained model submitted, and the results obtained by the team's inference code, then the team will not be allowed to continue the competition. The team results will not be displayed on the leaderboard in such a case.

The team member can upload the results only once.

The team member needs to upload results corresponding to a task.



Submission for Task A: Isolated Word Recognition in Low Resolution

Submission of Brief Description of Algorithm
  • Write a maximum of one page description of your proposed method to solve Isolated Word Recognition in Low Resolution tasks and name the file as (description.doc/description.pdf/description.txt/description.latex).
Submission of Results
  • The output should be saved as ‘result.txt’ which contains names of test word images and corresponding predictions separated by a tab in each line.
Submission of Trained Model
  • Create a zip file of the trained model and upload
Submission of Inference Code
  • Inference code, requirement.txt with software packages required to run the code, and ReadMe file with instructions for running the code. Make a zip file and upload it.

Select Team Name

 

Upload Result

 

Upload Inference Code

 

Upload Trained Model

 

Upload Brief Description of Algorithm

 

Use any Pretrained Model

 

Use any Additional Training Dataset

 

Use any Synthetic Data for Training

 

Use any Pre-processing Step to Clean the Training Dataset

 

Use any Post OCR Error Correction Technique to Improve OCR Accuracy

 
Submission for Dataset for Task B: Prediction of Reading Order

Submission of Brief Description of Algorithm
  • Write a maximum of one page description of your proposed method to Predict Reading Order of Words of a document and name the file as (description.doc/description.pdf/description.txt/description.latex).
Submission of Results
  • The output should be saved as '*.txt' (e.g., if the name of the test set is "1_1.txt", the corresponding output should be saved as "1_1_result.txt"), which contains bounding boxes of words, textual transcriptions (as present in the test set) and predicted sequence order separated by a tab in each line.
  • Create a folder that includes all results.
  • Make a zip and upload.
Submission of Trained Model
  • Create a zip file of the trained model and upload
Submission of Inference Code
  • Inference code, requirement.txt with software packages required to run the code, and ReadMe file with instructions for running the code. Make a zip file and upload it.

Select Team Name

 

Upload Result

 

Upload Inference Code

 

Upload Trained Model

 

Upload Brief Description of Algorithm

 

Use any Pretrained Model

 

Use any Additional Training Dataset

 

Use any Synthetic Data for Training

 

Use any Pre-processing Step to Clean the Training Dataset

 
Submission for Task C: Page Level Recognition and Reading

Submission of Brief Description of Algorithm
  • Write a maximum of one page description of your proposed method to solve Page Level Recognition and Reading tasks and name the file as (description.doc/description.pdf/description.txt/description.latex).
Submission of Results
  • There should be one output file corresponding to an image. The output should be saved as 'image name_result.txt' (e.g., for image "304.jpg", the predicted result should be saved as "304_result.txt"), which contains the predicted text of the complete page image.
  • Create a folder that contains all predicted text files corresponding to all test images, make a zip, and upload it.
Submission of Trained Model
  • Create a zip file of the trained model and upload
Submission of Inference Code
  • Inference code, requirement.txt with software packages required to run the code, and ReadMe file with instructions for running the code. Make a zip file and upload it.

Select Team Name

 

Upload Result

 

Upload Inference Code

 

Upload Trained Model

 

Upload Brief Description of Algorithm

 

Use any Pretrained Model

 

Use any Additional Training Dataset

 

Use any Synthetic Data for Training

 

Use any Pre-processing Step to Clean the Training Dataset

 

Use any Post OCR Error Correction Technique to Improve OCR Accuracy