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Commits on Aug 17, 2018

• updated readme

  justadudewhohacks

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• added allFaceTinyYolov2 + tiny yolov2 face recognition example

  justadudewhohacks

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• remove unused experimental tiny yolov2 model and prototxt of ssd_mobilenet from main repo

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• use the improved fps meter in all examples

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• weight loading of quantized tiny-yolov2-seperable-conv2d + use separable conv model by default + testcases

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• added test script to validate model accuracy on fddb benchmark

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• qunatized tiny_yolov2_separable_conv_model

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Commits on Aug 15, 2018

• merge with master

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Commits on Aug 14, 2018

• square images before converting them to tensors to prevent gpu memory leak issue

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• propagate exception in awaitMediaLoaded

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Commits on Aug 13, 2018

• 0.10.1

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• check in latest build

  justadudewhohacks

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• Merge pull request #70 from justadudewhohacks/#66

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• fixed image size overflowing in extractFaceTensors and extractFaces when rectangle overlaps image borders + testcases

  justadudewhohacks

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• fixed testcase for loading modelfile from external uri

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• Merge pull request #69 from bmaguireibm/master

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• check in latest training script

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• use fix for tf.maximum for now in leaky relu

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Commits on Aug 12, 2018

• check in latest train scripts

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Commits on Aug 10, 2018

• Adding test for external uri

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• Adding check for external protocol in uri

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• log individual loss types and average losses

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Commits on Aug 9, 2018

• fixed loss function

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• fixed masks and coordinate loss

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Commits on Aug 6, 2018

• rewrite loss function with tf ops, such that it's differentiable

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Commits on Aug 5, 2018

• init training function

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Commits on Aug 4, 2018

• init train data fetching

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• implemented yolo loss functions + mean subtraction for retrained model

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• prepare tinyYolov2 for using depthwise seperable conv2ds + retraining

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Commits on Jul 31, 2018

• 0.10.0

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• Merge pull request #62 from justadudewhohacks/tiny-yolov2

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• check in latest build

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• added tiny yolov2 usage and description to readme

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• Merge branch 'master' into tiny-yolov2

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• testcases for tinyYolov2

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