added kaggle comp solution for facial keypoint

ML/Kaggles/Facial Keypoint Detection Competition/config.py

@@ -0,0 +1,61 @@
+import torch
+import albumentations as A
+from albumentations.pytorch import ToTensorV2
+import cv2
+
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+LEARNING_RATE = 1e-4
+WEIGHT_DECAY = 5e-4
+BATCH_SIZE = 64
+NUM_EPOCHS = 100
+NUM_WORKERS = 4
+CHECKPOINT_FILE = "b0_4.pth.tar"
+PIN_MEMORY = True
+SAVE_MODEL = True
+LOAD_MODEL = True
+
+# Data augmentation for images
+train_transforms = A.Compose(
+    [
+        A.Resize(width=96, height=96),
+        A.Rotate(limit=15, border_mode=cv2.BORDER_CONSTANT, p=0.8),
+        A.IAAAffine(shear=15, scale=1.0, mode="constant", p=0.2),
+        A.RandomBrightnessContrast(contrast_limit=0.5, brightness_limit=0.5, p=0.2),
+        A.OneOf([
+            A.GaussNoise(p=0.8),
+            A.CLAHE(p=0.8),
+            A.ImageCompression(p=0.8),
+            A.RandomGamma(p=0.8),
+            A.Posterize(p=0.8),
+            A.Blur(p=0.8),
+        ], p=1.0),
+        A.OneOf([
+            A.GaussNoise(p=0.8),
+            A.CLAHE(p=0.8),
+            A.ImageCompression(p=0.8),
+            A.RandomGamma(p=0.8),
+            A.Posterize(p=0.8),
+            A.Blur(p=0.8),
+        ], p=1.0),
+        A.ShiftScaleRotate(shift_limit=0.1, scale_limit=0.1, rotate_limit=0, p=0.2, border_mode=cv2.BORDER_CONSTANT),
+        A.Normalize(
+            mean=[0.4897, 0.4897, 0.4897],
+            std=[0.2330, 0.2330, 0.2330],
+            max_pixel_value=255.0,
+        ),
+        ToTensorV2(),
+    ], keypoint_params=A.KeypointParams(format="xy", remove_invisible=False),
+)
+
+
+val_transforms = A.Compose(
+    [
+        A.Resize(height=96, width=96),
+        A.Normalize(
+            mean=[0.4897, 0.4897, 0.4897],
+            std=[0.2330, 0.2330, 0.2330],
+            max_pixel_value=255.0,
+        ),
+        ToTensorV2(),
+    ], keypoint_params=A.KeypointParams(format="xy", remove_invisible=False),
+)