ning8429 commited on
Commit
3787a8c
·
verified ·
1 Parent(s): 715f512

Update api_server.py

Browse files
Files changed (1) hide show
  1. api_server.py +24 -18
api_server.py CHANGED
@@ -39,14 +39,14 @@ elif load_type == 'remote_hub_download':
39
  # 從 Hugging Face Hub 下載模型
40
  model_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_NAME)
41
  model = torch.load(model_path)
42
- model.eval()
43
  elif load_type == 'remote_hub_from_pretrained':
44
  # 使用 Hugging Face Hub 預訓練的模型方式下載
45
  os.environ['TRANSFORMERS_CACHE'] = str(Path(MODEL_DIR).absolute())
46
  from huggingface_hub import from_pretrained
47
 
48
  model = from_pretrained(REPO_ID, filename=MODEL_NAME, cache_dir=MODEL_DIR)
49
- model.eval()
50
  else:
51
  raise AssertionError('No load type is specified!')
52
 
@@ -63,15 +63,14 @@ def get_jpg_files(path):
63
  """
64
  Args:
65
  path: 要搜尋的目錄路徑。
66
-
67
  Returns:
68
  一個包含所有 JPG 檔案路徑的列表。
69
  """
70
  return glob.glob(os.path.join(path, "*.jpg"))
71
 
72
  # 使用範例
73
- image_folder = '/content/drive/MyDrive/chiikawa' # 替換成你的目錄路徑
74
- jpg_files = get_jpg_files(image_folder)
75
 
76
 
77
  # Initialize the Flask application
@@ -84,7 +83,7 @@ def predict():
84
 
85
  #user_id = request.args.get('user_id')
86
  file = request.files['image']
87
- message_id = request.form.get('message_id') #str(uuid.uuid4()) # 生成一個唯一的 message_id
88
 
89
  if 'image' not in request.files:
90
  # Handle if no file is selected
@@ -121,18 +120,25 @@ def predict():
121
  element_list =[]
122
 
123
  for element, count in element_counts.items():
124
- if element_counts[element] > 1: #某隻角色的數量>1
125
- output_path = f"{YOLO_DIR}/{message_id}/{element}"
126
- output_file = get_jpg_files(output_path)
127
- element_list.append(element)
128
-
129
- for output_img in output_file: # 取得每張圖的路徑
130
- encoded_images.append(image_to_base64(output_img))
131
-
132
- else : #某隻角色的數量=1
133
- output_path = f"{YOLO_DIR}/{message_id}/{element}/im.jpg.jpg"
134
- encoded_images.append(image_to_base64(output_path))
135
- element_list.append(element)
 
 
 
 
 
 
 
136
 
137
  # 建立回應資料
138
  response_data = {
 
39
  # 從 Hugging Face Hub 下載模型
40
  model_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_NAME)
41
  model = torch.load(model_path)
42
+ #model.eval()
43
  elif load_type == 'remote_hub_from_pretrained':
44
  # 使用 Hugging Face Hub 預訓練的模型方式下載
45
  os.environ['TRANSFORMERS_CACHE'] = str(Path(MODEL_DIR).absolute())
46
  from huggingface_hub import from_pretrained
47
 
48
  model = from_pretrained(REPO_ID, filename=MODEL_NAME, cache_dir=MODEL_DIR)
49
+ #model.eval()
50
  else:
51
  raise AssertionError('No load type is specified!')
52
 
 
63
  """
64
  Args:
65
  path: 要搜尋的目錄路徑。
 
66
  Returns:
67
  一個包含所有 JPG 檔案路徑的列表。
68
  """
69
  return glob.glob(os.path.join(path, "*.jpg"))
70
 
71
  # 使用範例
72
+ # image_folder = '/content/drive/MyDrive/chiikawa' # 替換成你的目錄路徑
73
+ # jpg_files = get_jpg_files(image_folder)
74
 
75
 
76
  # Initialize the Flask application
 
83
 
84
  #user_id = request.args.get('user_id')
85
  file = request.files['image']
86
+ message_id = request.form.get('message_id') #str(uuid.uuid4())
87
 
88
  if 'image' not in request.files:
89
  # Handle if no file is selected
 
120
  element_list =[]
121
 
122
  for element, count in element_counts.items():
123
+
124
+ output_path = f"{YOLO_DIR}/{message_id}/{element}"
125
+ output_file = get_jpg_files(output_path)
126
+
127
+ element_list.append(element)
128
+
129
+ for output_img in output_file: # 取得每張圖的路徑
130
+ encoded_images.append(image_to_base64(output_img))
131
+
132
+ # if element_counts[element] > 1: #某隻角色的數量>1
133
+ # output_path = f"{YOLO_DIR}/{message_id}/{element}"
134
+ # output_file = get_jpg_files(output_path)
135
+
136
+ # for output_img in output_file: # 取得每張圖的路徑
137
+ # encoded_images.append(image_to_base64(output_img))
138
+
139
+ # else : #某隻角色的數量=1
140
+ # output_path = f"{YOLO_DIR}/{message_id}/{element}/im.jpg.jpg"
141
+ # encoded_images.append(image_to_base64(output_path))
142
 
143
  # 建立回應資料
144
  response_data = {