1. 17 May, 2021 2 commits
  2. 13 May, 2021 1 commit
  3. 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
      f87ce881
    • Nicolas Hug's avatar
      remove comment (#3807) · 9dbff560
      Nicolas Hug authored
      9dbff560
  4. 10 May, 2021 2 commits
  5. 04 May, 2021 2 commits
  6. 03 May, 2021 1 commit
  7. 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
  8. 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
  9. 27 Apr, 2021 2 commits
  10. 26 Apr, 2021 5 commits
  11. 23 Apr, 2021 4 commits
  12. 22 Apr, 2021 1 commit
  13. 21 Apr, 2021 2 commits
  14. 20 Apr, 2021 1 commit
  15. 19 Apr, 2021 1 commit
  16. 16 Apr, 2021 1 commit
  17. 12 Apr, 2021 2 commits
  18. 09 Apr, 2021 1 commit
    • Prabhat Roy's avatar
      Added KITTI dataset (#3640) · 7da9afee
      Prabhat Roy authored
      
      
      * Added KITTI dataset
      
      * Addressed review comments
      
      * Changed type of target to List[Dict] and corrected the data types of the returned values.
      
      * Updated unit test to rely on ImageDatasetTestCase
      
      * Added kitti to dataset documentation
      
      * Cleaned up test and some minor changes
      
      * Made data_url a string instead of a list
      
      * Removed unnecessary try and print
      Co-authored-by: default avatarFrancisco Massa <fvsmassa@gmail.com>
      7da9afee
  19. 08 Apr, 2021 1 commit
    • Nicolas Hug's avatar
      Add Quantized version of RoIAlign (#3624) · ad9cc62a
      Nicolas Hug authored
      * WIP
      
      * clang
      
      * docs
      
      * extracted out common utils
      
      * Use better quantization function and pass tensors as parameters
      
      * proper dequantization
      
      * Some tests
      
      * Dequantization optimization, seems to gain a few ms
      
      * clang-format
      
      * again
      
      * more correct test. Had to remove optimization although it almost works
      
      * Also test aligned=True
      
      * remove useless part
      
      * more docs and comments
      
      * Put back optimization with more robust test
      
      * Added check for index upper bound
      
      * avoid possible overflow
      
      * Move common function into common.h
      
      * oops
      
      * scale=1,zero_point=0 makes more sense
      
      * Force batch size of 1 to prevent any indexingbug
      
      * format
      
      * format again
      
      * updated docstring
      
      * put back description comment for pre_calc_bilinear_interpolate
      
      * revert most changes to docstring as it's taken care of in another PR
      ad9cc62a
  20. 06 Apr, 2021 1 commit
  21. 30 Mar, 2021 5 commits