update gallery2fc

ppcls/utils/gallery2fc.py

+import os
 import paddle
+
 from ppcls.arch import build_model
+from ppcls.arch.gears.identity_head import IdentityHead
 from ppcls.utils.config import parse_config, parse_args
 from ppcls.utils.save_load import load_dygraph_pretrain
 from ppcls.utils.logger import init_logger
+from ppcls.data import transform, create_operators
 
 
-def load_feature_extractor(configs):
-    arch = build_model(configs["Arch"])
-    load_dygraph_pretrain(arch, configs["Global"]["pretrained_model"])
+def build_gallery_feature(configs, feature_extractor):
+    transform_configs = configs["Infer"]["transforms"]
+    preprocess_ops = create_operators(transform_configs)
+
+    embedding_size = configs["Arch"]["Head"]["embedding_size"]
+    batch_size = configs["IndexProcess"]["batch_size"]
+    image_shape = configs["Global"]["image_shape"]
+    image_shape.insert(0, batch_size)
+    input_tensor = paddle.zeros(image_shape)
+
+    image_root = configs["IndexProcess"]["image_root"]
+    data_file = configs["IndexProcess"]["data_file"]
+    delimiter = configs["IndexProcess"]["delimiter"]
+    gallery_images = []
+    gallery_docs = []
+
+    with open(data_file, 'r', encoding='utf-8') as f:
+        lines = f.readlines()
+        for _, ori_line in enumerate(lines):
+            line = ori_line.strip().split(delimiter)
+            text_num = len(line)
+            assert text_num >= 2, f"line({ori_line}) must be splitted into at least 2 parts, but got {text_num}"
+            image_file = os.path.join(image_root, line[0])
+
+            gallery_images.append(image_file)
+            gallery_docs.append(ori_line.strip())
+
 
 
-def build_gallery_feature(feature_extractor):
-    pass
 
 
 def save_fuse_model(fuse_model):
@@ -21,11 +47,14 @@ def save_fuse_model(fuse_model):
 class FuseModel(paddle.nn.Layer):
     def __init__(self, configs):
         super().__init__()
-        self.feature_extractor = load_feature_extractor(configs)
-        self.gallery_layer = build_gallery_feature(self.feature_extractor)
+        self.feature_extractor = build_model(configs)
+        load_dygraph_pretrain(self.feature_extractor, configs["Global"]["pretrained_model"])
+        self.feature_extractor.head = IdentityHead()
+        self.gallery_layer = build_gallery_feature(configs, self.feature_extractor)
 
     def forward(self, x):
-        x = self.feature_model(x)
+        x = self.feature_model(x)["features"]
+        x = paddle.norm(x)
         x = self.gallery_layer(x)
         return x