search

blessedlex / Skynet-Zuckerberg-Edition

CYBR 4580-8950 IA Capstone Project
0 stars 0 forks source link

use Facebook's default training models to test DeepMask algorithm #21

Open blessedlex opened 3 years ago

blessedlex commented 3 years ago

findings posted here

blessedlex commented 3 years ago

For a training size of 5,000: th train.lua

For a training size of 4,000: th train.lua -batch 25

For a training size of 1,000: th train.lua -batch 7

For evaluating each model: th evalPerImage.lua /model/path

For a training size of 100%: train_nGPU=1 ./scripts/train_multipathnet_coco.sh

For a training size of 80%: train_nGPU=1 batchSize=51 ./scripts/train_multipathnet_coco.sh

For a training size of 20%: train_nGPU=1 batchSize=13 ./scripts/train_multipathnet_coco.sh

For evaluation: test_nGPU=1 test_nsamples=5000 ./scripts/eval_coco.sh

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.244 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.402 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.268 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.394 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.249 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.368 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.135 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.444 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.561