# Test Server Evaluation on COCO dataset This page walks through the steps required to convert DeepLab2 predictions for test server evaluation on [COCO](https://cocodataset.org/). A high-level overview of the whole process: 1. Save raw panoptic prediction in the two-channel format. 2. Convert predictions in the two-channel format to the panoptic COCO format. 3. Run local validation set evaluation or prepare test set evaluation. We also define some environmental variables for simplicity and convenience: `BASE_MODEL_DIRECTORY`: variables set in textproto file, which defines where all checkpoints and results are saved. `DATA_ROOT`: where the original COCO dataset is located. `PATH_TO_SAVE`: where the converted results should be saved. ## Save Raw Panoptic Prediction Save the raw panoptic predictions in the [two-channel panoptic format](https://arxiv.org/pdf/1801.00868.pdf) by ensuring the following fields are set properly in the textproto config file. ``` eval_dataset_options.decode_groundtruth_label = false evaluator_options.save_predictions = true evaluator_options.save_raw_predictions = true evaluator_options.convert_raw_to_eval_ids = true ``` Then run the model in evaluation modes (with `--mode=eval`), and the results will be saved at ${BASE_MODEL_DIRECTORY}/vis/raw_panoptic/\*.png. ## Convert the Prediction Format Convert prediction results saved in the [two-channel panoptic format](https://arxiv.org/pdf/1801.00868.pdf) to the panoptic COCO format. ```bash python panopticapi/converters/2channels2panoptic_coco_format.py \ --source_folder=${BASE_MODEL_DIRECTORY}/vis/raw_panoptic \ --images_json_file=${DATA_ROOT}/annotations/IMG_JSON \ --categories_json_file=panopticapi/panoptic_coco_categories.json \ --segmentations_folder=${PATH_TO_SAVE}/panoptic_cocoformat \ --predictions_json_file=${PATH_TO_SAVE}/panoptic_cocoformat.json ``` The `IMG_JSON` refers to `panoptic_val2017.json` for *val* set and `image_info_test-dev2017.json` for *test-dev* set. ## Run Local Evaluation Scripts (for *validation* set) Run the [official scripts](https://github.com/cocodataset/panopticapi) to evaluate validation set results. ```bash python panopticapi/evaluation.py \ --pred_json_file=${PATH_TO_SAVE}/panoptic_cocoformat.json \ --pred_folder=${PATH_TO_SAVE}/panoptic_cocoformat \ --gt_json_file=${DATA_ROOT}/annotations/panoptic_val2017.json \ --gt_folder=${DATA_ROOT}/annotations/panoptic_val2017 ``` ## Prepare Submission Files (for *test* set) Run the following command to prepare a submission file for test server evaluation. ```bash zip -r coco_test_submission_panoptic.zip ${PATH_TO_SAVE}/panoptic_cocoformat ${PATH_TO_SAVE}/panoptic_cocoformat.json ```