Inferencing over several datasets with one specs file?

I am wondering whether it is possible to apply inferencing on several datasets with one specs file. It’s a bit annoying to turn on a docker at each time (3 minutes for startup) for a couple of minutes of inferencing. Putting all data in the same folder is not an option as it really mixes up things for me, especially naming the outputs.

inference_config {
images_dir: '/workspace/tao-experiments/data/training/Lightly/testing/image_2'
batch_size: 1
bbox_caption_on: True
detection_image_output_dir: '/workspace/inf/inference_results_imgs'
labels_dump_dir: '/workspace/inf/inference_dump_labels'
rpn_pre_nms_top_N: 6000
rpn_nms_max_boxes: 300
rpn_nms_overlap_threshold: 0.9
object_confidence_thres: 0.0001 #0.0001
bbox_visualize_threshold: 0.6
classifier_nms_max_boxes: 100
classifier_nms_overlap_threshold: 0.0001

I am using a FasterRCNN.

For instance, is it possible to have two inference_config entries? or several image_dir, detection_image_output_dir and labels_dump_dir in one entry?


Currently, the Faster_rcnn inference script can support one folder only.
For this feature, you can try to modify the code( to meet expectation.
Assume there are below structure,


You can change line 128 to

128  folder_path = spec.inference_images_dir

And also add a logic on the top of
For example,

folder_set = os.listdir(folder_path)
for subfolder in folder_set:
    if os.path.isdir(os.path.join(folder_path, subfolder)):
        img_path = os.path.join(folder_path, subfolder)
        image_set = os.listdir(img_path)

You can also need to handle and output dirs(

Thanks for your input Morgan :). Appreciate it.

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