mtcnn - Fix for torch

torzdf · Mar 1, 2024 · 739459a · 739459a
1 parent 4a78639
commit 739459a
Showing 1 changed file with 7 additions and 7 deletions.
diff --git a/plugins/extract/detect/mtcnn.py b/plugins/extract/detect/mtcnn.py
@@ -7,7 +7,7 @@
 import cv2
 import numpy as np
 
-from keras.layers import Conv2D, Dense, Flatten, Input, MaxPool2D, Permute, PReLU
+from keras.layers import Conv2D, Dense, Flatten, Input, MaxPooling2D, Permute, PReLU
 
 from lib.model.session import KSession
 from ._base import BatchType, Detector
@@ -185,7 +185,7 @@ def model_definition() -> tuple[list[Tensor], list[Tensor]]:
         input_ = Input(shape=(None, None, 3))
         var_x = Conv2D(10, (3, 3), strides=1, padding='valid', name='conv1')(input_)
         var_x = PReLU(shared_axes=[1, 2], name='PReLU1')(var_x)
-        var_x = MaxPool2D(pool_size=2)(var_x)
+        var_x = MaxPooling2D(pool_size=2)(var_x)
         var_x = Conv2D(16, (3, 3), strides=1, padding='valid', name='conv2')(var_x)
         var_x = PReLU(shared_axes=[1, 2], name='PReLU2')(var_x)
         var_x = Conv2D(32, (3, 3), strides=1, padding='valid', name='conv3')(var_x)
@@ -351,11 +351,11 @@ def model_definition() -> tuple[list[Tensor], list[Tensor]]:
         input_ = Input(shape=(24, 24, 3))
         var_x = Conv2D(28, (3, 3), strides=1, padding='valid', name='conv1')(input_)
         var_x = PReLU(shared_axes=[1, 2], name='prelu1')(var_x)
-        var_x = MaxPool2D(pool_size=3, strides=2, padding='same')(var_x)
+        var_x = MaxPooling2D(pool_size=3, strides=2, padding='same')(var_x)
 
         var_x = Conv2D(48, (3, 3), strides=1, padding='valid', name='conv2')(var_x)
         var_x = PReLU(shared_axes=[1, 2], name='prelu2')(var_x)
-        var_x = MaxPool2D(pool_size=3, strides=2)(var_x)
+        var_x = MaxPooling2D(pool_size=3, strides=2)(var_x)
 
         var_x = Conv2D(64, (2, 2), strides=1, padding='valid', name='conv3')(var_x)
         var_x = PReLU(shared_axes=[1, 2], name='prelu3')(var_x)
@@ -475,13 +475,13 @@ def model_definition() -> tuple[list[Tensor], list[Tensor]]:
         input_ = Input(shape=(48, 48, 3))
         var_x = Conv2D(32, (3, 3), strides=1, padding='valid', name='conv1')(input_)
         var_x = PReLU(shared_axes=[1, 2], name='prelu1')(var_x)
-        var_x = MaxPool2D(pool_size=3, strides=2, padding='same')(var_x)
+        var_x = MaxPooling2D(pool_size=3, strides=2, padding='same')(var_x)
         var_x = Conv2D(64, (3, 3), strides=1, padding='valid', name='conv2')(var_x)
         var_x = PReLU(shared_axes=[1, 2], name='prelu2')(var_x)
-        var_x = MaxPool2D(pool_size=3, strides=2)(var_x)
+        var_x = MaxPooling2D(pool_size=3, strides=2)(var_x)
         var_x = Conv2D(64, (3, 3), strides=1, padding='valid', name='conv3')(var_x)
         var_x = PReLU(shared_axes=[1, 2], name='prelu3')(var_x)
-        var_x = MaxPool2D(pool_size=2)(var_x)
+        var_x = MaxPooling2D(pool_size=2)(var_x)
         var_x = Conv2D(128, (2, 2), strides=1, padding='valid', name='conv4')(var_x)
         var_x = PReLU(shared_axes=[1, 2], name='prelu4')(var_x)
         var_x = Permute((3, 2, 1))(var_x)