scene_graph_benchmark/tools/demo/demo_image.py
, and now I only need jpg
image dataset, VinVl yaml configuration file and model weight file. The predictions are saved in dictionary and are stored in pth
format. I ran it on Google Colab and it generates predictions at a rate about 2s/image. I hope this helps.
#51
Hi, I found a way to circumvent using tsv files by modifying
scene_graph_benchmark/tools/demo/demo_image.py
, and now I only needjpg
image dataset, VinVl yaml configuration file and model weight file. The predictions are saved in dictionary and are stored inpth
format. I ran it on Google Colab and it generates predictions at a rate about 2s/image. I hope this helps.Originally posted by @SPQRXVIII001 in #7 (comment)
The text was updated successfully, but these errors were encountered: