1

app.py

@@ -5,8 +5,8 @@ import numpy as np
 
 
 # 모델과 특징 추출기 불러오기
-feature_extractor = SegformerFeatureExtractor.from_pretrained("nvidia/segformer-b5-finetuned-cityscapes-1024-1024")
-model = SegformerForSemanticSegmentation.from_pretrained("nvidia/segformer-b5-finetuned-cityscapes-1024-1024")
+feature_extractor = SegformerFeatureExtractor.from_pretrained("nvidia/segformer-b0-finetuned-cityscapes-512-1024")
+model = SegformerForSemanticSegmentation.from_pretrained("nvidia/segformer-b0-finetuned-cityscapes-512-1024")
 
 def segment_image(image):
     # 이미지를 처리하고 모델에 전달하기

config.json

@@ -4,12 +4,12 @@
   ],
   "attention_probs_dropout_prob": 0.0,
   "classifier_dropout_prob": 0.1,
-  "decoder_hidden_size": 768,
+  "decoder_hidden_size": 256,
   "depths": [
-    3,
-    6,
-    40,
-    3
+    2,
+    2,
+    2,
+    2
   ],
   "downsampling_rates": [
     1,
@@ -21,10 +21,10 @@
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.0,
   "hidden_sizes": [
+    32,
     64,
-    128,
-    320,
-    512
+    160,
+    256
   ],
   "id2label": {
     "0": "road",

preprocessor_config.json

@@ -14,5 +14,5 @@
   ],
   "reduce_labels": false,
   "resample": 2,
-  "size": 1024
+  "size": 512
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 338896453
+oid sha256:ec0a4ad8388261a33e9fad6045feabf8b0f764bba6fc5511397fe39714400a91
+size 14957601

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e210af2d6d0dfb7eabecfcb1831845830b762a04d65d69e879cfc17288a11540
-size 339967916
+oid sha256:296ed1fbafabfe8ed5a1875c5a42bdcb0d22d552145e610f4f6fa4215123af5a
+size 15151028