v0.4

What's Changed

• v0.3.5 by @LukeWood in #1123
• [Object Detection] Update backbone structure for FasterRCNN by @ianstenbit in #1122
• Fix a bug in gourp_points_by_bounding_boxes data augmentation by @lengzq in #1126
• Add get_config to all 3d data augmentations by @lengzq in #1127
• Skip waymo tests in devcontainer by @ianstenbit in #1125
• Fix bugs in frustum-based data augmentations by @lengzq in #1135
• Adding ViT Models by @DavidLandup0 in #1014
• [Preprocessing] Migrate RandomContrast to KerasCV by @ianstenbit in #1133
• Fix GPU testing by @chenmoneygithub in #1142
• Migrate RandomCrop to Keras CV by @divyashreepathihalli in #1141
• ViT Name Refactor by @DavidLandup0 in #1143
• Format weight conversion script by @LukeWood in #1149
• Migrate RandomZoom by @divyashreepathihalli in #1136
• Fix typo in iou_3d docs by @ianstenbit in #1147
• [RetinaNet Refactor] Step 1 Fix bug and Reuse box delta encoding and decoding logic. by @tanzhenyu in #1152
• (Step 4/5) Add KPLs to RetinaNet training script by @LukeWood in #1148
• [Preprocessing] Migrate RandomBrightness to KerasCV by @ianstenbit in #1138
• fix forward for RetinaNet. by @tanzhenyu in #1155
• [Backbones] Update basic_training to support weight decay and ema by @ianstenbit in #1124
• [Refactor RetinaNet] Step 2 Use label dict in label encoder and base model. by @tanzhenyu in #1156
• pin bazel version by @tanzhenyu in #1165
• [Refactor RetinaNet] Step 3, Batch implementation of label encoding. by @tanzhenyu in #1163
• Migrate VGG16 to keras_cv.models by @IMvision12 in #1164
• Separating MBConvBlock, FusedMBConvBlock and Refactoring EfficientNetV2 by @DavidLandup0 in #1146
• [Refactor RetinaNet] Step 4 Encode labels in model forward pass. by @tanzhenyu in #1173
• Switch to new EfficientNet weights (post-PR #1146) by @ianstenbit in #1151
• [Refactor RetinaNet] Step 5 remove the inheritance from ObjectDetectionBaseModel. by @tanzhenyu in #1175
• Add black jupyter extension and fix skip tests without custom ops by @bhack in #1150
• Gate Waymo-dependent tests with a flag by @ianstenbit in #1177
• Add an internal UNet implementation by @ianstenbit in #1167
• Add missing serialization params for two layers by @ianstenbit in #1178
• [Refactor RetinaNet] Step 6 Unify FasterRCNN to decode during predict. by @tanzhenyu in #1182
• Fix bug in GlobalRandomDroppingPoints by @lengzq in #1160
• Reduce unit test dataset size for OD models by @ianstenbit in #1185
• [Refactor RetinaNet] Step 8 Unify FasterRCNN NMS decode to return dict. by @tanzhenyu in #1187
• [Refactor RetinaNet] Step 7, unify nms decoder outputs for both models. by @tanzhenyu in #1194
• add voxelization layer. by @tanzhenyu in #1186
• [Codebase Consistency] MLPMixer Refactoring by @DavidLandup0 in #1024
• Improve FlipY by @lengzq in #1195
• Add support for Stable Diffusion 2.1 by @Jobayer-000 in #1130
• [Refactor RetinaNet] Step 9 unify NMSDecoder. by @tanzhenyu in #1197
• [0.4 Release SemSeg] Refactor Deeplab to be a functional subclassing model by @DavidLandup0 in #1119
• Basic Semantic Segmentation Training Script by @DavidLandup0 in #1183
• [3D Object Detection] Waymo Evaluation Callback by @ianstenbit in #1129
• Upgrade to the last TF stable version by @bhack in #1170
• Fix gpu tests after pinning bazel version in #1188 by @ianstenbit in #1199
• Make GPU CI tests run custom op tests by @ianstenbit in #1200
• Update release process to build wheels with custom ops by @ianstenbit in #1188
• Adding ViT weights by @DavidLandup0 in #1145
• Add ABI warning to custom ops loader by @ianstenbit in #1201
• [Refactor RetinaNet] Step 10, Unify call and loss reduction for Retin… by @tanzhenyu in #1204
• add center_net_label_encoder by @tanzhenyu in #1202
• [Object Detection] Remove backbone_weights from RetinaNet by @ianstenbit in #1203
• Add pretrained weights for ResNet50 by @ianstenbit in #1211
• Add top-5 accuracy for imagenet training script by @ianstenbit in #1212
• [Refactor FasterRCNN] remove unknown batch size restriction to be ready for Functional Subc… by @tanzhenyu in #1208
• [RetinaNet training] init optimizer inside strategy scope by @ianstenbit in #1213
• Migrate Rescaling to Keras_CV by @divyashreepathihalli in #1209
• Fix weights typo for ResNet50 by @ianstenbit in #1215
• [Object Detection] Use functional subclass paradigm for RetinaNet by @ianstenbit in #1205
• Revert "[Object Detection] Use functional subclass paradigm for RetinaNet" by @ianstenbit in #1216
• RCNN model API finalization. by @tanzhenyu in #1217
• RetinaNet API Finalization by @ianstenbit in #1218
• Update version to 0.4 by @ianstenbit in #1219

New Contributors

• @chenmoneygithub made their first contribution in #1142
• @IMvision12 made their first contribution in #1164
• @Jobayer-000 made their first contribution in #1130

Full Changelog: v0.3.5...v0.4