llava_mistral_0531 / client /images_client_batch.py
root
feat
14bd491
from PIL import Image
import os
import time
import requests
import base64
import numpy as np
from io import BytesIO
import concurrent.futures
NUM_SEGMENTS = 10
tic = time.time()
video_dir = '/home/ubuntu/shared_storage/images'
frames = [(os.path.splitext(item)[0], os.path.join(video_dir, item)) for item in os.listdir(video_dir)]
frames = [item[1] for item in sorted(frames, key=lambda x: x[0])]
indices = np.linspace(start=0, stop=len(frames)-1, num=NUM_SEGMENTS).astype(int)
image_paths = [frames[ind] for ind in indices]
request = {}
byte_images = []
def image_path_handler(image_path):
img = Image.open(image_path)
byte_io = BytesIO()
img.save(byte_io, format='PNG')
encoded_image = base64.b64encode(byte_io.getvalue()).decode('utf-8')
return encoded_image
with concurrent.futures.ThreadPoolExecutor() as executor:
byte_images = list(executor.map(image_path_handler, image_paths))
payload = {
"images": byte_images * 16,
"parameters": {
"max_new_tokens": 90,
"top_k": 4,
"top_p": None,
"temperature": 0.01,
"no_repeat_ngram_size": None,
}
}
IP = '127.0.0.1'
url = f'http://{IP}:8000/generate'
headers = {'Content-Type': 'application/json'}
tic1 = time.time()
response = requests.post(url, json=payload, headers=headers)
toc = time.time()
print(response.text)
print('stage 1', tic1 - tic)
print('stage 2', toc - tic1)