- 25 May, 2021 1 commit
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Vasilis Vryniotis authored
* Fix a bug when trainable_layers == 0 * Fix same issue on ssd.
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- 18 May, 2021 1 commit
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Nicolas Hug authored
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- 12 May, 2021 1 commit
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Vasilis Vryniotis authored
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- 03 May, 2021 1 commit
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Vasilis Vryniotis authored
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- 30 Apr, 2021 1 commit
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Vasilis Vryniotis authored
* Early skeleton of API. * Adding MultiFeatureMap and vgg16 backbone. * Making vgg16 backbone same as paper. * Making code generic to support all vggs. * Moving vgg's extra layers a separate class + L2 scaling. * Adding header vgg layers. * Fix maxpool patching. * Refactoring code to allow for support of different backbones & sizes: - Skeleton for Default Boxes generator class - Dynamic estimation of configuration when possible - Addition of types * Complete the implementation of DefaultBox generator. * Replace randn with empty. * Minor refactoring * Making clamping between 0 and 1 optional. * Change xywh to xyxy encoding. * Adding parameters and reusing objects in constructor. * Temporarily inherit from Retina to avoid dup code. * Implement forward methods + temp workarounds to inherit from retina. * Inherit more methods from retinanet. * Fix type error. * Add Regression loss. * Fixing JIT issues. * Change JIT workaround to minimize new code. * Fixing initialization bug. * Add classification loss. * Update todos. * Add weight loading support. * Support SSD512. * Change kernel_size to get output size 1x1 * Add xavier init and refactoring. * Adding unit-tests and fixing JIT issues. * Add a test for dbox generator. * Remove unnecessary import. * Workaround on GeneralizedRCNNTransform to support fixed size input. * Remove unnecessary random calls from the test. * Remove more rand calls from the test. * change mapping and handling of empty labels * Fix JIT warnings. * Speed up loss. * Convert 0-1 dboxes to original size. * Fix warning. * Fix tests. * Update comments. * Fixing minor bugs. * Introduce a custom DBoxMatcher. * Minor refactoring * Move extra layer definition inside feature extractor. * handle no bias on init. * Remove fixed image size limitation * Change initialization values for bias of classification head. * Refactoring and update test file. * Adding ResNet backbone. * Minor refactoring. * Remove inheritance of retina and general refactoring. * SSD should fix the input size. * Fixing messages and comments. * Silently ignoring exception if test-only. * Update comments. * Update regression loss. * Restore Xavier init everywhere, update the negative sampling method, change the clipping approach. * Fixing tests. * Refactor to move the losses from the Head to the SSD. * Removing resnet50 ssd version. * Adding support for best performing backbone and its config. * Refactor and clean up the API. * Fix lint * Update todos and comments. * Adding RandomHorizontalFlip and RandomIoUCrop transforms. * Adding necessary checks to our tranforms. * Adding RandomZoomOut. * Adding RandomPhotometricDistort. * Moving Detection transforms to references. * Update presets * fix lint * leave compose and object * Adding scaling for completeness. * Adding params in the repr * Remove unnecessary import. * minor refactoring * Remove unnecessary call. * Give better names to DBox* classes * Port num_anchors estimation in generator * Remove rescaling and fix presets * Add the ability to pass a custom head and refactoring. * fix lint * Fix unit-test * Update todos. * Change mean values. * Change the default parameter of SSD to train the full VGG16 and remove the catch of exception for eval only. * Adding documentation * Adding weights and updating readmes. * Update the model weights with a more performing model. * Adding doc for head. * Restore import.
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