75 lines
1.5 KiB
Python
75 lines
1.5 KiB
Python
import json
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import requests
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import base64
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import time
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import os
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import sys
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sys.path.append("../../../middleware_api/lambda/inference")
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from parse.parameter_parser import json_convert_to_payload
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from dotenv import load_dotenv
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load_dotenv()
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start_time = time.time()
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# prepare payload
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task_type = ''
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payload_checkpoint_info = json.loads(os.environ['checkpoint_info'])
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f = open("../json_files/aigc.json")
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params_dict = json.load(f)
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payload = json_convert_to_payload(params_dict, payload_checkpoint_info, task_type)
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print(payload.keys())
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# # call local api
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# url = "http://localhost:8082"
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# print("docker api test for clip:")
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# with open("test.png", "rb") as img:
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# test_img = str(base64.b64encode(img.read()), 'utf-8')
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# payload = {
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# "task": "interrogate_clip",
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# "interrogate_payload": {
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# "image":test_img,
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# "model":"clip"
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# }
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# }
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# #
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# response = requests.post(url=f'{url}/invocations', json=payload)
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# print(f"run time is {time.time()-start_time}")
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# r = response.json()
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# prompt_message = r["caption"]
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# print(f"prompt message : {prompt_message}")
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# print("docker api test for deepbooru:")
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# payload = {
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# "task": "interrogate_deepbooru",
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# "interrogate_payload": {
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# "image":test_img,
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# "model":"deepdanbooru"
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# }
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# }
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# #
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# response = requests.post(url=f'{url}/invocations', json=payload)
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# print(f"run time is {time.time()-start_time}")
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# r = response.json()
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# prompt_message = r["caption"]
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# print(f"prompt message : {prompt_message}")
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