updated image segmentation data prep example. Runs end-to-end with downloadable data.
"source": [
"Each input image in `raw` uses a 256 x 256 matrix of pixel _BGR_ values to define a visual picture. Each corresponding ground truth image in `mask` uses a 256 x 256 matrix of pixel _object class_ values, resulting in a pixel-by-pixel object class map. The number of classes required for an image segmentation ground truth map is equal to the number of object classes plus 1. \n",
"\n",
- "The image segmentation model in this example detects two object classes in input images: _player_ and _ball_. Every input image pixel BGR array corresponds to a matching ground truth pixel-wise object class array. Each ground truth image pixel contains a class value: it must be 0 (background), or 1 (player), or 2 (ball). \n",
+ "The image segmentation model in this example detects two object classes in input images: _player_ and _ball_. Every input image pixel BGR array corresponds to a matching ground truth pixel-wise object class array. Each ground truth image pixel contains a class value: it must be 0 (background), or 1 (player), or 2 (background). \n",
"\n",
"Each pixel in the input image array specifies a 24-bit color defined by combined 8-bit values for blue, green, and red components. Each pixel in the ground truth array references an object class ID using only integers [0, 1, 2]. \n",
"\n",
"\n",
"### Join the Raw and Mask CAS Tables\n",
"\n",
- "Use the SAS CAS `dljoin()` function to merge the `raw` image and `mask` ground truth tables into a single training table. Use the `_filename_0` column as the join index. Name the merged model training table `segTrainTbl_1`. It will be suitable for training image segmentation models."
+ "Use the SAS CAS `dljoin()` action to merge the `raw` image and `mask` ground truth tables into a single training table. Use the `_filename_0` column as the join index. Name the merged model training table `segTrainTbl_1`. It will be suitable for training image segmentation models."
]
},
{
"\n",
"The steps to perform this task are consolidated in the time- and effort-saving SAS DLPy `create_segmentation_table()` function.\n"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
}
],
"metadata": {
