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  1. 25 May, 2021 4 commits
  3. 24 May, 2021 3 commits
  5. 22 May, 2021 2 commits
  7. 21 May, 2021 14 commits
  9. 20 May, 2021 1 commit
  11. 19 May, 2021 1 commit
  13. 17 May, 2021 4 commits
  15. 13 May, 2021 1 commit
  17. 11 May, 2021 3 commits
    • Vasilis Vryniotis's avatar
      Add SSDlite architecture with MobileNetV3 backbones (#3757) · 43d77206
      Vasilis Vryniotis authored 
      * Partial implementation of SSDlite.

* Add normal init and BN hyperparams.

* Refactor to keep JIT happy

* Completed SSDlite.

* Fix lint

* Update todos

* Add expected file in repo.

* Use C4 expansion instead of C4 output.

* Change scales formula for Default Boxes.

* Add cosine annealing on trainer.

* Make T_max count epochs.

* Fix test and handle corner-case.

* Add support of support width_mult

* Add ssdlite presets.

* Change ReLU6, [-1,1] rescaling, backbone init & no pretraining.

* Use _reduced_tail=True.

* Add sync BN support.

* Adding the best config along with its weights and documentation.

* Make mean/std configurable.

* Fix not implemented for half exception
      43d77206
    • Nicolas Hug's avatar
      Support for decoding jpegs on GPU with nvjpeg (#3792) · f87ce881
      Nicolas Hug authored 
      
Co-authored-by: default avatarJames Thewlis <james@unitary.ai>
      f87ce881
    • Nicolas Hug's avatar
      remove comment (#3807) · 9dbff560
      Nicolas Hug authored
      9dbff560
  19. 10 May, 2021 2 commits
  21. 04 May, 2021 2 commits
  23. 03 May, 2021 1 commit
  25. 30 Apr, 2021 1 commit
    • Vasilis Vryniotis's avatar
      Add SSD architecture with VGG16 backbone (#3403) · 730c5e1e
      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.
      730c5e1e
  27. 28 Apr, 2021 1 commit
    • Nicolas Hug's avatar
      [FBcode->GH] Parametrize test_perspective (#3748) (#3749) · 1b0bd0e3
      Nicolas Hug authored 
      Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/3748

This PR parametrizes the `perspective`-related tests, and avoids having deeply nested for-loops which will help debugging. "What" gets tested is left unchanged.

The newly-introduced `cpu_and_gpu()` generator along with the `dont_collect` mark is a logic that allows to not run CPU tests on GPU machines (and vice versa).

Reviewed By: fmassa

Differential Revision: D27908299

fbshipit-source-id: 24a10a89fe90ae0a9e62de4bc7e768a669ebf212
      1b0bd0e3