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Update api_server.py
Browse files- api_server.py +24 -18
api_server.py
CHANGED
@@ -39,14 +39,14 @@ elif load_type == 'remote_hub_download':
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# 從 Hugging Face Hub 下載模型
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model_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_NAME)
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model = torch.load(model_path)
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model.eval()
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elif load_type == 'remote_hub_from_pretrained':
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# 使用 Hugging Face Hub 預訓練的模型方式下載
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os.environ['TRANSFORMERS_CACHE'] = str(Path(MODEL_DIR).absolute())
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from huggingface_hub import from_pretrained
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model = from_pretrained(REPO_ID, filename=MODEL_NAME, cache_dir=MODEL_DIR)
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model.eval()
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else:
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raise AssertionError('No load type is specified!')
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@@ -63,15 +63,14 @@ def get_jpg_files(path):
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"""
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Args:
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path: 要搜尋的目錄路徑。
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Returns:
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一個包含所有 JPG 檔案路徑的列表。
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"""
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return glob.glob(os.path.join(path, "*.jpg"))
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# 使用範例
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image_folder = '/content/drive/MyDrive/chiikawa' # 替換成你的目錄路徑
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jpg_files = get_jpg_files(image_folder)
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# Initialize the Flask application
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@@ -84,7 +83,7 @@ def predict():
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#user_id = request.args.get('user_id')
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file = request.files['image']
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message_id = request.form.get('message_id') #str(uuid.uuid4())
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if 'image' not in request.files:
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# Handle if no file is selected
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@@ -121,18 +120,25 @@ def predict():
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element_list =[]
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for element, count in element_counts.items():
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# 建立回應資料
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response_data = {
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# 從 Hugging Face Hub 下載模型
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model_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_NAME)
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model = torch.load(model_path)
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#model.eval()
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elif load_type == 'remote_hub_from_pretrained':
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# 使用 Hugging Face Hub 預訓練的模型方式下載
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os.environ['TRANSFORMERS_CACHE'] = str(Path(MODEL_DIR).absolute())
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from huggingface_hub import from_pretrained
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model = from_pretrained(REPO_ID, filename=MODEL_NAME, cache_dir=MODEL_DIR)
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#model.eval()
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else:
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raise AssertionError('No load type is specified!')
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"""
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Args:
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path: 要搜尋的目錄路徑。
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Returns:
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一個包含所有 JPG 檔案路徑的列表。
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"""
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return glob.glob(os.path.join(path, "*.jpg"))
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# 使用範例
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# image_folder = '/content/drive/MyDrive/chiikawa' # 替換成你的目錄路徑
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# jpg_files = get_jpg_files(image_folder)
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# Initialize the Flask application
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#user_id = request.args.get('user_id')
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file = request.files['image']
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message_id = request.form.get('message_id') #str(uuid.uuid4())
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if 'image' not in request.files:
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# Handle if no file is selected
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element_list =[]
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for element, count in element_counts.items():
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output_path = f"{YOLO_DIR}/{message_id}/{element}"
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output_file = get_jpg_files(output_path)
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element_list.append(element)
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for output_img in output_file: # 取得每張圖的路徑
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encoded_images.append(image_to_base64(output_img))
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# if element_counts[element] > 1: #某隻角色的數量>1
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# output_path = f"{YOLO_DIR}/{message_id}/{element}"
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# output_file = get_jpg_files(output_path)
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# for output_img in output_file: # 取得每張圖的路徑
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# encoded_images.append(image_to_base64(output_img))
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# else : #某隻角色的數量=1
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# output_path = f"{YOLO_DIR}/{message_id}/{element}/im.jpg.jpg"
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# encoded_images.append(image_to_base64(output_path))
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# 建立回應資料
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response_data = {
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