OrgLion-ML
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openface
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Tweak classifier.py interface and show usage in the README.

This commit is contained in:
Brandon Amos 2015-10-11 17:35:50 -04:00
parent 23f0860e47
commit 71be06d81e
2 changed files with 12 additions and 3 deletions
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7
README.md
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@ -230,6 +230,13 @@ the confidence score is usually lower.
| Carell | <img src='images/examples/carell.jpg' width='200px'></img> | SteveCarell | 0.78 | | Carell | <img src='images/examples/carell.jpg' width='200px'></img> | SteveCarell | 0.78 |
| Adams | <img src='images/examples/adams.jpg' width='200px'></img> | AmyAdams | 0.87 | | Adams | <img src='images/examples/adams.jpg' width='200px'></img> | AmyAdams | 0.87 |
Run this on new images with:
```
./demos/classifier.py ./models/openface/celeb-classifier.nn4.v1.pkl infer <image>
```
# Model Definitions # Model Definitions
Model definitions should be kept in [models/openface](models/openface), Model definitions should be kept in [models/openface](models/openface),
where we have provided definitions of the [nn1](models/openface/nn1.def.lua) where we have provided definitions of the [nn1](models/openface/nn1.def.lua)

8
demos/classifier.py
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@ -96,7 +96,7 @@ def train(args):
pickle.dump((le, svm), f) pickle.dump((le, svm), f)
def infer(args): def infer(args):
with open("{}/classifier.pkl".format(args.workDir), 'r') as f: with open(args.classifierModel, 'r') as f:
(le, svm) = pickle.load(f) (le, svm) = pickle.load(f)
rep = getRep(args.img) rep = getRep(args.img)
predictions = svm.predict_proba(rep)[0] predictions = svm.predict_proba(rep)[0]
@ -108,8 +108,6 @@ def infer(args):
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('workDir', type=str,
help="The input work directory containing 'reps.csv' and 'labels.csv'. Obtained from aligning a directory with 'align-dlib' and getting the representations with 'batch-represent'.")
parser.add_argument('--dlibFaceMean', type=str, parser.add_argument('--dlibFaceMean', type=str,
help="Path to dlib's face predictor.", help="Path to dlib's face predictor.",
default=os.path.join(dlibModelDir, "mean.csv")) default=os.path.join(dlibModelDir, "mean.csv"))
@ -131,8 +129,12 @@ if __name__ == '__main__':
subparsers = parser.add_subparsers(dest='mode', help="Mode") subparsers = parser.add_subparsers(dest='mode', help="Mode")
trainParser = subparsers.add_parser('train', trainParser = subparsers.add_parser('train',
help="Train a new classifier.") help="Train a new classifier.")
trainParser.add_argument('workDir', type=str,
help="The input work directory containing 'reps.csv' and 'labels.csv'. Obtained from aligning a directory with 'align-dlib' and getting the representations with 'batch-represent'.")
inferParser = subparsers.add_parser('infer', inferParser = subparsers.add_parser('infer',
help='Predict who an image contains from a trained classifier.') help='Predict who an image contains from a trained classifier.')
inferParser.add_argument('classifierModel', type=str)
inferParser.add_argument('img', type=str, inferParser.add_argument('img', type=str,
help="Input image.") help="Input image.")