forked from cgvr/DeltaVR
added more time logging to python script + switched to using CGVR lab WiFi
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@@ -6,6 +6,7 @@ import json
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import logging
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import httpx
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import os
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import time
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from typing import Optional
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from urllib.parse import urljoin
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@@ -493,6 +494,8 @@ async def text_to_image_invoke_ai(prompt, output_path):
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"model_key": INVOKEAI_MODEL_KEY
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}
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image_url = await generate_image(args)
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print("Got image url:", image_url)
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print("Downloading image file...")
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print("Downloading image from", image_url)
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time_start = time.time()
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download_file(image_url, output_path)
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download_time = time.time() - time_start
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print(f"Image downloaded in {round(download_time, 1)} seconds")
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@@ -32,7 +32,7 @@ def generate_no_preview(image_base64: str):
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}
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# Start generation
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print("Starting generation...")
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print("Generating model...")
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response = requests.post(f"{API_URL}/generate_no_preview", data=params)
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response.raise_for_status()
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@@ -50,8 +50,11 @@ def generate_no_preview(image_base64: str):
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# Download the model
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print("Downloading model...")
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time_start = time.time()
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response = requests.get(f"{API_URL}/download/model")
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response.raise_for_status()
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time_download = time.time() - time_start
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print(f"Model downloaded in {round(time_download, 1)} seconds")
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return response.content
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@@ -41,8 +41,6 @@ async def main():
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time_checkpoint = time.time()
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image_path = pipeline_folder / "images" / f"{timestamp}.jpg"
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# TODO: use Invoke AI or Cloudflare, depending on env var
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#text_to_image_cloudflare(image_generation_prompt, image_path)
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await text_to_image_invoke_ai(image_generation_prompt, image_path)
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image_generation_time = time.time() - time_checkpoint
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