Merge pull request #27 from tomas-gajarsky/feature/adaface

tomas-gajarsky · web-flow · commit 095da6933228 · 2022-11-18T16:33:43.000+01:00
Feature/adaface
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,12 @@
 # Change Log
 
+## 0.1.4
+
+Released on November 18, 2022.
+
+### Added
+* predictor for face verification and face recognition - AdaFace by Kim et al.
+
 
 ## 0.1.3
 
diff --git a/README.md b/README.md
@@ -110,14 +110,22 @@ analyzer
 
 #### Face Verification (verify)
 
-    |    verify     |    source    |      license       | version |  
-    | ------------- |  ----------- | ------------------ | ------- |
-    |  MagFace+UNPG |  Jung-Jun-Uk | Apache License 2.0 |    1    |
+    |      verify      |   source    |      license       | version |  
+    | ---------------- | ----------- | ------------------ | ------- |
+    |    MagFace+UNPG  | Jung-Jun-Uk | Apache License 2.0 |    1    |
+    |  AdaFaceR100W12M |  mk-minchul |     MIT License    |    2    |
 
 1. Jung-Jun-Uk
     * code: [UNPG](https://github.com/jung-jun-uk/unpg)
     * paper: [Jung et al. - Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition](https://arxiv.org/abs/2203.11593)
-    * [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/unified-negative-pair-generation-toward-well/face-verification-on-ijb-b)](https://paperswithcode.com/sota/face-verification-on-ijb-b?p=unified-negative-pair-generation-toward-well)
+    * [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/unified-negative-pair-generation-toward-well/face-verification-on-ijb-b)](https://paperswithcode.com/sota/face-verification-on-ijb-b?p=unified-negative-pair-generation-toward-well)(FAR=0.01)
+    * Note: ```include_tensors``` needs to be True in order to include the model prediction in Prediction.logits
+2. mk-minchul
+    * code: [AdaFace](https://github.com/mk-minchul/adaface)
+    * paper: [Kim et al. - AdaFace: Quality Adaptive Margin for Face Recognition](https://arxiv.org/abs/2204.00964)
+    * [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/adaface-quality-adaptive-margin-for-face/face-verification-on-ijb-b)](https://paperswithcode.com/sota/face-verification-on-ijb-b?p=adaface-quality-adaptive-margin-for-face) <
+    * [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/adaface-quality-adaptive-margin-for-face/face-verification-on-ijb-c)](https://paperswithcode.com/sota/face-verification-on-ijb-c?p=adaface-quality-adaptive-margin-for-face) <
+    * < badges represent models trained on smaller WebFace 4M dataset
     * Note: ```include_tensors``` needs to be True in order to include the model prediction in Prediction.logits
 
 
@@ -170,7 +178,7 @@ You can also download the models manually from a [public Google Drive folder](ht
 
 ### Execution time
 
-Image test.jpg (4 faces) is analyzed (including drawing boxes and landmarks, but not saving) in about 440ms and test3.jpg (25 faces) in about 1416ms (batch_size=8) on NVIDIA Tesla T4 GPU once the default configuration (*conf/config.yaml*) of models is initialized and pre heated to the initial image size 1080x1080 by the first run. One can monitor the execution times in logs using the DEBUG level.
+Image test.jpg (4 faces) is analyzed (including drawing boxes and landmarks, but not saving) in about 465ms and test3.jpg (25 faces) in about 1480ms (batch_size=8) on NVIDIA Tesla T4 GPU once the default configuration (*conf/config.yaml*) of models is initialized and pre heated to the initial image size 1080x1080 by the first run. One can monitor the execution times in logs using the DEBUG level.
 
 Detailed test.jpg execution times:
 ```
@@ -180,7 +188,7 @@ analyzer
     ├── unifier: 1 ms
     └── predictor
             ├── embed: 8 ms
-            ├── verify: 18 ms
+            ├── verify: 58 ms
             ├── fer: 28 ms
             ├── deepfake: 117 ms
             └── align: 5 ms
diff --git a/conf/analyzer/predictor/embed/r50_vggface_1m.yaml b/conf/analyzer/predictor/embed/r50_vggface_1m.yaml
@@ -21,7 +21,7 @@ preprocessor:
         std: [0.228, 0.224, 0.225] # List[float]
   device: 
     _target_: torch.device
-    type: ${analyzer.predictor.fer.device.type}
+    type: ${analyzer.predictor.embed.device.type}
   optimize_transform: ${analyzer.optimize_transforms}
   reverse_colors: False # bool
 
@@ -30,6 +30,6 @@ postprocessor:
   transform: None
   device: 
     _target_: torch.device
-    type: ${analyzer.predictor.fer.device.type}
+    type: ${analyzer.predictor.embed.device.type}
   optimize_transform: ${analyzer.optimize_transforms}
   labels: ["abstract"] # List
diff --git a/conf/analyzer/predictor/verify/adaface_ir101_webface12m.yaml b/conf/analyzer/predictor/verify/adaface_ir101_webface12m.yaml
@@ -0,0 +1,35 @@
+_target_: facetorch.analyzer.predictor.FacePredictor
+
+downloader:
+  _target_: facetorch.downloader.DownloaderGDrive
+  file_id: 1WI-mP_0mGW31OHfriPUsuFS_usYh_W8p
+  path_local: /opt/facetorch/models/torchscript/predictor/verify/2/model.pt # str
+
+device:
+  _target_: torch.device
+  type: ${analyzer.device} # str
+
+preprocessor:
+  _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
+  transform:
+    _target_: torchvision.transforms.Compose
+    transforms:
+      - _target_: torchvision.transforms.Resize
+        size: [112, 112] # List[int]
+      - _target_: torchvision.transforms.Normalize
+        mean: [0.5, 0.5, 0.5] # List[float]
+        std: [0.5, 0.5, 0.5] # List[float]
+  device: 
+    _target_: torch.device
+    type: ${analyzer.predictor.verify.device.type}
+  optimize_transform: ${analyzer.optimize_transforms}
+  reverse_colors: True # bool
+
+postprocessor:
+  _target_: facetorch.analyzer.predictor.post.PostEmbedder
+  transform: None
+  device: 
+    _target_: torch.device
+    type: ${analyzer.predictor.verify.device.type}
+  optimize_transform: ${analyzer.optimize_transforms}
+  labels: ["abstract"] # List
diff --git a/conf/analyzer/predictor/verify/r100_magface_unpg.yaml b/conf/analyzer/predictor/verify/r100_magface_unpg.yaml
@@ -21,7 +21,7 @@ preprocessor:
         std: [0.229, 0.224, 0.225] # List[float]
   device: 
     _target_: torch.device
-    type: ${analyzer.predictor.fer.device.type}
+    type: ${analyzer.predictor.verify.device.type}
   optimize_transform: ${analyzer.optimize_transforms}
   reverse_colors: False # bool
 
@@ -30,6 +30,6 @@ postprocessor:
   transform: None
   device: 
     _target_: torch.device
-    type: ${analyzer.predictor.fer.device.type}
+    type: ${analyzer.predictor.verify.device.type}
   optimize_transform: ${analyzer.optimize_transforms}
   labels: ["abstract"] # List
diff --git a/conf/config.yaml b/conf/config.yaml
@@ -4,7 +4,7 @@ defaults:
   - analyzer/detector: retinaface.yaml
   - analyzer/unifier: img_380.yaml
   - analyzer/predictor/embed: r50_vggface_1m.yaml
-  - analyzer/predictor/verify: r100_magface_unpg.yaml
+  - analyzer/predictor/verify: adaface_ir101_webface12m.yaml
   - analyzer/predictor/fer: efficientnet_b2_8.yaml
   - analyzer/predictor/deepfake: efficientnet_b7.yaml
   - analyzer/predictor/align: synergy_mobilenet_v2.yaml
diff --git a/conf/tests.config.1.yaml b/conf/tests.config.1.yaml
@@ -4,7 +4,7 @@ defaults:
   - analyzer/detector: retinaface.yaml
   - analyzer/unifier: img_380.yaml
   - analyzer/predictor/embed: r50_vggface_1m.yaml
-  - analyzer/predictor/verify: r100_magface_unpg.yaml
+  - analyzer/predictor/verify: adaface_ir101_webface12m.yaml
   - analyzer/predictor/fer: efficientnet_b2_8.yaml
   - analyzer/predictor/deepfake: efficientnet_b7.yaml
   - analyzer/predictor/align: synergy_mobilenet_v2.yaml
diff --git a/conf/tests.config.3.yaml b/conf/tests.config.3.yaml
@@ -4,7 +4,7 @@ defaults:
   - analyzer/detector: retinaface.yaml
   - analyzer/unifier: img_380.yaml
   - analyzer/predictor/embed: r50_vggface_1m.yaml
-  - analyzer/predictor/verify: r100_magface_unpg.yaml
+  - analyzer/predictor/verify: adaface_ir101_webface12m.yaml
   - analyzer/predictor/fer: efficientnet_b2_8.yaml
   - analyzer/predictor/deepfake: efficientnet_b7.yaml
   - analyzer/predictor/align: synergy_mobilenet_v2.yaml
diff --git a/conf/tests.config.4.yaml b/conf/tests.config.4.yaml
@@ -4,7 +4,7 @@ defaults:
   - analyzer/detector: retinaface.yaml
   - analyzer/unifier: img_380.yaml
   - analyzer/predictor/embed: r50_vggface_1m.yaml
-  - analyzer/predictor/verify: r100_magface_unpg.yaml
+  - analyzer/predictor/verify: adaface_ir101_webface12m.yaml
   - analyzer/predictor/fer: efficientnet_b2_8.yaml
   - analyzer/predictor/deepfake: efficientnet_b7.yaml
   - analyzer/predictor/align: synergy_mobilenet_v2.yaml
diff --git a/tests/test_detector.py b/tests/test_detector.py
@@ -13,7 +13,6 @@ def test_downloader_run(analyzer):
         os.remove(analyzer.detector.downloader.path_local)
     analyzer.detector.downloader.run()
     assert os.path.exists(analyzer.detector.downloader.path_local)
-    os.remove(analyzer.detector.downloader.path_local)
 
 
 @pytest.mark.integration
diff --git a/tests/test_predictors.py b/tests/test_predictors.py
@@ -10,8 +10,8 @@
 @pytest.mark.downloader
 def test_downloaders_run(analyzer):
     for predictor in analyzer.predictors.values():
-        if os.path.exists(predictor.downloader.path_local):
-            os.remove(predictor.downloader.path_local)
+        # if os.path.exists(predictor.downloader.path_local):
+        # os.remove(predictor.downloader.path_local)
         predictor.downloader.run()
         assert os.path.exists(predictor.downloader.path_local)
 
diff --git a/version b/version
@@ -1 +1 @@
-0.1.3
+0.1.4
