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File size: 2,172 Bytes
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import os
import cv2
import base64
import requests
import numpy as np
from tqdm import tqdm
from pathlib import Path
from zipfile import ZipFile
def download_and_unzip_model(root_dir:str, name:str,
url:str, file_size:int, unzip:bool = False):
'''
Checking model in model_path
download model if file not found
@params:
root_dir(str): The root directory of model.
name(str): The name of model.
url(str): The url of model.
file_size(int): The size of model.
unzip(bool): Unzip the model or not.
'''
Path(root_dir).mkdir(parents=True, exist_ok=True)
# check if model is already or not
print(f'Downloading {root_dir.split("/")[-1]} model, please wait.')
response = requests.get(url, stream=True)
progress = tqdm(response.iter_content(1024),
f'Downloading model',
total=file_size, unit='B',
unit_scale=True, unit_divisor=1024)
save_dir = f'{root_dir}/{name}'
with open(save_dir, 'wb') as f:
for data in progress:
f.write(data)
progress.update(len(data))
print(f'Done downloading {root_dir.split("/")[-1]} model.')
# unzip model
if unzip:
with ZipFile(save_dir, 'r') as zip_obj:
zip_obj.extractall(root_dir)
print(f'Done unzip {root_dir.split("/")[-1]} model.')
os.remove(save_dir)
def encode_image2string(image):
image_list = cv2.imencode('.jpg', image)[1]
image_bytes = image_list.tobytes()
image_encoded = base64.b64encode(image_bytes)
return image_encoded
def decode_string2image(image_encoded):
jpg_original = base64.b64decode(image_encoded)
jpg_as_np = np.frombuffer(jpg_original, dtype=np.uint8)
image = cv2.imdecode(jpg_as_np, flags=1)
return image
def resize_image(image, size_percent):
'''
Resize an image so that its longest edge equals to the given size.
Args:
image(cv2.Image): The input image.
size_percent(int): The size of longest edge.
Returns:
image(cv2.Image): The output image.
'''
width = int(image.shape[1] * size_percent / 100)
height = int(image.shape[0] * size_percent / 100)
dim = (width, height)
# resize image
resized = cv2.resize(image, dim, interpolation = cv2.INTER_AREA)
return resized |