Merge pull request #188885 from mispa-ms/mispa/masktool_args

add masktool args

Author: PRMerger12

articles/machine-learning/how-to-auto-train-image-models.md

@@ -493,8 +493,9 @@ Each of the tasks (and some models) have a set of parameters in the `model_setti
 | Task | Parameter name | Default  |
 |--------- |------------- | --------- |
 |Image classification (multi-class and multi-label) | `valid_resize_size`<br>`valid_crop_size` | 256<br>224 |
-|Object detection, instance segmentation| `min_size`<br>`max_size`<br>`box_score_thresh`<br>`nms_iou_thresh`<br>`box_detections_per_img` | 600<br>1333<br>0.3<br>0.5<br>100 |
+|Object detection | `min_size`<br>`max_size`<br>`box_score_thresh`<br>`nms_iou_thresh`<br>`box_detections_per_img` | 600<br>1333<br>0.3<br>0.5<br>100 |
 |Object detection using `yolov5`| `img_size`<br>`model_size`<br>`box_score_thresh`<br>`nms_iou_thresh` | 640<br>medium<br>0.1<br>0.5 |
+|Instance segmentation| `min_size`<br>`max_size`<br>`box_score_thresh`<br>`nms_iou_thresh`<br>`box_detections_per_img`<br>`mask_pixel_score_threshold`<br>`max_number_of_polygon_points`<br>`export_as_image`<br>`image_type` | 600<br>1333<br>0.3<br>0.5<br>100<br>0.5<br>100<br>False<br>JPG|
 
 For a detailed description on task specific hyperparameters, please refer to [Hyperparameters for computer vision tasks in automated machine learning](reference-automl-images-hyperparameters.md).
 

articles/machine-learning/reference-automl-images-hyperparameters.md

@@ -32,6 +32,15 @@ This table summarizes hyperparameters specific to the `yolov5` algorithm.
 | `box_score_thresh` | During inference, only return proposals with a score greater than `box_score_thresh`. The score is the multiplication of the objectness score and classification probability. <br> Must be a float in the range [0, 1]. | 0.1 |
 | `nms_iou_thresh` | IOU threshold used during inference in non-maximum suppression post processing. <br> Must be a float in the range [0, 1]. | 0.5 |
 
+This table summarizes hyperparameters specific to the `maskrcnn_*` for instance segmentation during inference.
+
+| Parameter name       | Description           | Default  |
+| ------------- |-------------|----|
+| `mask_pixel_score_threshold` | Score cutoff for considering a pixel as part of the mask of an object. | 0.5 |
+| `max_number_of_polygon_points` | Maximum number of (x, y) coordinate pairs in polygon after converting from a mask. | 100 |
+| `export_as_image` | Export masks as images. | False |
+| `image_type` | Type of image to export mask as (options are jpg, png, bmp).  | JPG |
+
 ## Model agnostic hyperparameters
 
 The following table describes the hyperparameters that are model agnostic.