Update the PATH of CASIA and lfw in FaceNet (#288) (#296)

demo/slimfacenet/slim_eval.sh

@@ -15,5 +15,5 @@
 #!/bin/bash
 export CUDA_VISIBLE_DEVICES=0
 python train_eval.py --action test \
-    --train_data_dir=/PATH_TO_CASIA_Dataset \
-    --test_data_dir=/PATH_TO_lfw \
+    --train_data_dir=./CASIA/ \
+    --test_data_dir=./lfw/ \

demo/slimfacenet/slim_quant.sh

@@ -15,5 +15,6 @@
 #!/bin/bash
 export CUDA_VISIBLE_DEVICES=0
 python train_eval.py --action quant \
-    --train_data_dir=/PATH_TO_CASIA_Dataset \
-    --test_data_dir=/PATH_TO_lfw \
+    --train_data_dir=./CASIA/ \
+    --test_data_dir=./lfw/ \
+    --seed=1

demo/slimfacenet/slim_train.sh

@@ -15,7 +15,7 @@
 #!/bin/bash
 export CUDA_VISIBLE_DEVICES=0
 python -u train_eval.py \
-    --train_data_dir=/PATH_TO_CASIA_Dataset \
-    --test_data_dir=/PATH_TO_LFW \
+    --train_data_dir=./CASIA/ \
+    --test_data_dir=./lfw/ \
     --action train \
     --model=SlimFaceNet_B_x0_75

demo/slimfacenet/train_eval.py

@@ -120,6 +120,7 @@ def train(exe, train_program, train_out, test_program, test_out, args):
     compiled_prog = compiler.CompiledProgram(
         train_program, build_strategy=build_strategy).with_data_parallel(
             loss_name=loss.name, build_strategy=build_strategy)
+    best_ave = 0
     for epoch_id in range(args.start_epoch, args.total_epoch):
         for batch_id, data in enumerate(train_reader()):
             loss, acc, global_lr = exe.run(compiled_prog,
@@ -135,14 +136,17 @@ def train(exe, train_program, train_out, test_program, test_out, args):
             model_path = os.path.join(args.save_ckpt, str(epoch_id))
             fluid.io.save_persistables(
                 executor=exe, dirname=model_path, main_program=train_program)
-            test(exe, test_program, test_out, args)
-    out_feature, test_reader, flods, flags = test_out
-    fluid.io.save_inference_model(
-        executor=exe,
-        dirname='./out_inference',
-        feeded_var_names=['image_test'],
-        target_vars=[out_feature],
-        main_program=test_program)
+            temp_ave = test(exe, test_program, test_out, args)
+            if temp_ave > best_ave:
+                best_ave = temp_ave
+                print('Best AVE: {}'.format(best_ave))
+                out_feature, test_reader, flods, flags = test_out
+                fluid.io.save_inference_model(
+                    executor=exe,
+                    dirname='./out_inference',
+                    feeded_var_names=['image_test'],
+                    target_vars=[out_feature],
+                    main_program=test_program)
 
 
 def build_program(program, startup, args, is_train=True):
@@ -229,7 +233,9 @@ def quant_val_reader_batch():
     test_dataset = LFW(nl, nr)
     test_reader = paddle.batch(
         test_dataset.reader, batch_size=1, drop_last=False)
-    shuffle_reader = fluid.io.shuffle(test_reader, 1)
+    shuffle_index = args.seed if args.seed else np.random.randint(1000)
+    print('shuffle_index: {}'.format(shuffle_index))
+    shuffle_reader = fluid.io.shuffle(test_reader, shuffle_index)
 
     def _reader():
         while True:
@@ -283,6 +289,7 @@ def main():
         '--start_epoch', default=0, type=int, help='start_epoch')
     parser.add_argument(
         '--total_epoch', default=80, type=int, help='total_epoch')
+    parser.add_argument('--seed', default=None, type=int, help='shuffle seed')
     parser.add_argument(
         '--save_frequency', default=1, type=int, help='save_frequency')
     parser.add_argument(

paddleslim/models/slimfacenet.py

@@ -362,7 +362,7 @@ def SlimFaceNet_B_x0_75(class_dim=None, scale=0.6, arch=None):
 
 def SlimFaceNet_C_x0_75(class_dim=None, scale=0.6, arch=None):
     scale = 0.75
-    arch = [1, 1, 2, 1, 0, 2, 1, 0, 1, 0, 1, 1, 2, 2, 3]
+    arch = [1, 3, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 5, 5, 5]
     return SlimFaceNet(class_dim=class_dim, scale=scale, arch=arch)