pml 2.3.0 and review updates

README.md

@@ -3340,7 +3340,7 @@ Additional information about the evaluation kits, and the software development k
 
 [AHB Addresses for MAX78000 and MAX78002](docs/AHBAddresses.md)
 
-[Facial Recognition System](docs/FacialRecognitionSystem.md)
+[Facial Recognition System](https://github.com/MaximIntegratedAI/ai8x-training/blob/develop/docs/FacialRecognitionSystem.md)
 
 
 ---

datasets/vggface2.py

@@ -141,6 +141,9 @@ def __len__(self):
         return len(self.pickle_dict["img_list"]) - 1
 
     def __getitem__(self, index):
+        """
+        Get the image and associated target according to the mode
+        """
         if index >= len(self):
             raise IndexError
 
@@ -157,7 +160,9 @@ def __getitem__(self, index):
         return None
 
     def __getitem_detection(self, index):
-
+        """
+        Get the image and associated target for face detection
+        """
         if torch.is_tensor(index):
             index = index.tolist()
 
@@ -181,7 +186,9 @@ def __getitem_detection(self, index):
         return img, (boxes, labels)
 
     def __getitem_identification(self, index):
-
+        """
+        Get the image and associated target for face identification
+        """
         if torch.is_tensor(index):
             index = index.tolist()
 
@@ -246,7 +253,9 @@ def __getitem_identification(self, index):
         return concat_img, lbl_index
 
     def __getitem_identification_dr(self, index):
-
+        """
+        Get the image and associated target for dimensionality reduction
+        """
         if torch.is_tensor(index):
             index = index.tolist()
 

requirements.txt

@@ -19,10 +19,10 @@ albumentations>=1.3.0
 pytube>=12.1.3
 pyffmpeg==2.0
 GitPython>=3.1.18
-pytorch-metric-learning==1.6.3
+pytorch-metric-learning==2.3.0
 faiss-cpu==1.7.4
 hawk-eyes==2.1.2
-onnx==1.14.1
+onnx==1.15.0
 onnxruntime-gpu==1.10.0
 imutils==0.5.4
 -e distiller

scripts/train_facedet_tinierssd.sh

@@ -1,2 +1,2 @@
 #!/bin/sh
-python train.py --deterministic --print-freq 100 --epochs 3 --optimizer Adam --lr 1e-3 --wd 5e-4 --model ai85tinierssdface --use-bias --momentum 0.9 --dataset VGGFace2_FaceDetection --device MAX78000 --obj-detection --obj-detection-params parameters/obj_detection_params_facedet.yaml --batch-size 100 --qat-policy policies/qat_policy_facedet.yaml --validation-split 0.1 --gpus 1 "$@"
+python train.py --deterministic --print-freq 100 --epochs 3 --optimizer Adam --lr 1e-3 --wd 5e-4 --model ai85tinierssdface --use-bias --momentum 0.9 --dataset VGGFace2_FaceDetection --device MAX78000 --obj-detection --obj-detection-params parameters/obj_detection_params_facedet.yaml --batch-size 100 --qat-policy policies/qat_policy_facedet.yaml --validation-split 0.1 "$@"

train.py

@@ -1010,7 +1010,7 @@ def scaf_test(val_loader, model, accuracy_calculator):
     test_embeddings, test_labels = get_all_embeddings(val_loader.dataset, model)
     test_labels = test_labels.squeeze(1)
     accuracies = accuracy_calculator.get_accuracy(
-        test_embeddings, test_embeddings, test_labels, test_labels, True
+        test_embeddings, test_labels, None, None, True
     )
     msglogger.info('Test set accuracy (Precision@1) = %f', accuracies['precision_at_1'])
     return accuracies["precision_at_1"], 0, 0, 0