Downloading results
If you are interested in downstream statistical analysis that isn't yet available on Biodock, we allow any of your analytical results to be exported easily.

Downloading out AI-generated object metrics

Click on the Download data dropdown on the Top-level widget in the Results Dashboard. This will have a dropdown - select CSV data. This will give you access to a CSV file that contains extracted metrics per object, represented by each row.

Downloading out AI-generated object masks

Click on the Download data dropdown on the Top-level widget in the Results Dashboard. This will have a dropdown - select Mask data. This mask data will be downloaded in a compact JSON format that can be parsed with scripts and used for further computational analysis. The format is as follows:
example.json
{
"resultId": "AAAAAAAA-AAAA-AAAA-AAAA-AAAAAAAAAAA",
"dateRun": "2022-08-08T19:03:06.458Z",
"imageData": [
{
"filename": "file1.tif",
"id": "AAAAAAAAAAAAAAAAAAAAAAAA",
"height": 12288,
"width": 16384,
"objects": {
"1": {
"bbox": [ 250, 474, 437, 664 ], // x1, y1, x2, y2
"id": 1,
"rle": { // RLE-encoded object, use https://github.com/cocodataset/cocoapi to decode
"size": [ 190, 187 ],
"counts": "WWUwOFo1YTBLMEk7RDlGPE0w="
},
"pred_class": "Cyst",
"derived_objects": {}
}
}
}
],
"classData": {
"Cyst": {
"name": "Cyst",
"type": "Instance"
}
}
}

Processing Biodock output masks

Biodock output masks are encoded in a COCO-style RLE format. You can use cocoapi tools in Python, Lua, or Matlab to parse them easily. Some basic examples are below in Python - check out the Github repo for further documentation or for other languages

Installing pycocotools

pip install pycocotools # or conda install -c conda-forge pycocotools

Parsing Biodock output masks for an image into an array of binary masks

import pycocotools.mask as maskutil
import json
mask_results = json.load('masks.json')
first_image_objects_encoded = mask_results["imageData"][0]["objects"]
first_object_masks = []
for obj in first_image_objects_encoded.values():
first_object_masks = maskutil.decode(obj)
You can then convert these binary masks into polygons using a number of different libraries, and then, for example into FIJI using the ROI importer

Downloading high-resolution overlay images

If you are interested in downloading high-resolution images with overlaid masks, you can click Download button
in the Image Viewer window in Results Dashboard.
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On this page
Downloading out AI-generated object metrics
Downloading out AI-generated object masks
Downloading high-resolution overlay images