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Changed ambigious "optimization" references.
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herobd committed Sep 10, 2019
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14 changes: 7 additions & 7 deletions README.md
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Expand Up @@ -5,7 +5,7 @@ This is the code from our ICDAR 2019 paper, "Deep Visual Template-free Form Pars
This code is licensed under GNU GPL v3. If you would like it distributed to you under a different license, please contact me (briandavis@byu.net).

## Requirements
* Python 3.x (at least 3.7 for doing optimization)
* Python 3.x (at least 3.7 for doing global pairing optimization)
* PyTorch 1.0+

I used conda, but it shouldn't be hard to install the packages another way.
Expand All @@ -26,7 +26,7 @@ Run this in the Visual-Template-Free-Form-Parsing directoty: `python setup.py bu

### CVXPY

To run the optimization, you need cvxpy, which requires python 3.7 or later:
To run the global pairing optimization, you need cvxpy, which requires python 3.7 or later:

Clone github: https://github.com/cvxgrp/cvxpy

Expand Down Expand Up @@ -57,10 +57,10 @@ Detection, full set: `python eval.py -c saved/detector/checkpoint-iteration15000

Detection, pairing set: `python eval.py -c saved/detector/checkpoint-iteration150000.pth -n 0 -T -a data_loader=special_dataset=simple`

Pairing, no optimization: `python eval.py -c saved/pairing/checkpoint-iteration125000.pth -n 0 -T`
Pairing, no pairing optimization: `python eval.py -c saved/pairing/checkpoint-iteration125000.pth -n 0 -T`
`

Pairing, with optimization: `python eval.py -c saved/pairing/checkpoint-iteration125000.pth -n 0 -T -a optimize=true`
Pairing, with pairing optimization: `python eval.py -c saved/pairing/checkpoint-iteration125000.pth -n 0 -T -a optimize=true`

#### Perfect information experiments

Expand Down Expand Up @@ -97,7 +97,7 @@ Scoring functions pairing: `python eval.py -f cf_test_no_vis_pairing.json -n 0 -

No visual features pairing: `python eval.py -f cf_test_no_vis_pairing.json -n 0 -T`

No visual features pairing, with optimization: `python eval.py -f cf_test_no_vis_pairing.json -n 0 -T -a optimize=true`
No visual features pairing, with global optimization: `python eval.py -f cf_test_no_vis_pairing.json -n 0 -T -a optimize=true`

#### Perfect information experiments

Expand All @@ -109,7 +109,7 @@ For GT detections:

`python eval.py -f cf_test_no_vis_pairing.json -n 0 -T -a useDetect=gt`

For optimization with GT num neighbors:
For global optimization with GT num neighbors:

`python eval.py -f cf_test_no_vis_pairing.json -n 0 -T -a rule=closest,optimize=gt`

Expand Down Expand Up @@ -151,7 +151,7 @@ Evaluating detector:
Evaluatring pairing:
* `-a useDetect=[gt,path]`: Whether to use GT detections (`gt`) or can be directory with jsons with saved detections.
* `-a rule=[closest,icdar]`: Use a rule (nearest or scoring functions) to do pairing (instead of model).
* `-a optimize=[true,gt]`: Use optimization. If `gt` specified it will use the GT number of neighbors.
* `-a optimize=[true,gt]`: Use global pairing optimization. If `gt` specified it will use the GT number of neighbors.
* `-a penalty=[float]`: The variable *c* in Equation 1. Default is 0.25
* `-a THRESH=[float]`: Modify the thresh for calculating prec/recall for relationships. Also is *T* in Equation 1. Default is 0.7
* `-a sweep_threshold=true`: Run metrics using a range of thresholds
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