Spaces:
Sleeping
Sleeping
File size: 7,717 Bytes
21ba534 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 |
import logging
import os
import random
from datetime import datetime
from typing import List
from src.components.image_generation import batch_image_generation
from src.components.supabase_information_fetch import fetch_necklace_offset_each_store, fetch_model_body_type, \
upload_information_to_new_table, upload_productpage_logs
from src.components.video_generation import generate_combined_video
os.makedirs('logs', exist_ok=True)
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler('logs/running.log'),
logging.StreamHandler()
]
)
def update_processed_necklaces(necklace_id: str, status: bool, model_name: str):
response = upload_productpage_logs(necklace_id, status, model_name=model_name)
def get_random_clothing_combinations(clothing_list: List[str], colors: List[str], count: int = 5) -> List[str]:
"""Generate random clothing combinations."""
combinations = []
for _ in range(count):
clothing = random.choice(clothing_list)
color = random.choice(colors)
combinations.append(f"{color} {clothing}")
return combinations
def combined_image_and_video_generation(storename, image_url):
logging.info("Starting combined image and video generation process")
try:
necklace_data = fetch_necklace_offset_each_store(storename=storename)
url, typee = fetch_model_body_type(image_url=image_url)
model_name = url.split("/")[-1].split(".")[0]
for necklace in necklace_data:
necklace_id = necklace.necklace_id
response = upload_productpage_logs(necklace_id, True, model_name=model_name)
if response['status'] == "error":
print("Skipping", necklace_id)
logging.info(f"Skipping {necklace_id} - already processed")
continue
start_time = datetime.now()
logging.info(f"Processing necklace: {necklace_id}")
try:
if typee == "lean":
x_offset = necklace.x_lean_offset
y_offset = necklace.y_lean_offset
logging.info("Body Type: lean")
elif typee == "medium":
x_offset = necklace.x_broad_offset
y_offset = necklace.y_broad_offset
logging.info("Body Type: medium")
else:
logging.info("Body Type: None")
x_offset = None
y_offset = None
clothing_combinations = get_random_clothing_combinations(
clothing_list=["Salwar Kameez", "South Indian Saree", "Kurti", "Lehenga", "Silk Saree"],
colors=["Red", "Blue", "Green", "Yellow", "Pink"]
)
makeup_data = {
"lipstick": "Carmine Red",
"eyeliner": "Black",
"eyeshadow": "Maroon"
}
image_params = {
"model_image": url,
"necklace_id": necklace_id,
"necklace_category": necklace.category,
"storename": storename,
"clothing_list": clothing_combinations,
"makeup_colors": makeup_data,
"x_offset": x_offset,
"y_offset": y_offset
}
print("image: params", image_params)
logging.info("NTO-CTO-MTO images Generating for {}".format(necklace_id))
image_results = batch_image_generation(**image_params)
logging.info(f"Image generation result: {image_results}")
if image_results.status != 'success':
raise Exception(f"Image generation failed: {image_results.message}")
cto_urls = [result['url'] for result in image_results.cto_results[:4]] # First four CTO images
mto_urls = [image_results.mto_results[-1]['url']]
video_params = {
"intro_video_path": f"{storename}_intro.mp4",
"font_path": "PlayfairDisplay-VariableFont.ttf",
"background_audio_path": "LoveIndianCinematicBGM.mp3",
"necklace_title": [necklace_id],
"necklace_images": [necklace.necklace_url],
"nto_image_title": [[necklace_id]],
"nto_cto_image_title": [[necklace_id, necklace_id, necklace_id, necklace_id]],
"makeup_image_title": [[necklace_id]],
"necklace_try_on_output_images": [[result['url'] for result in image_results.nto_results]],
"clothing_output_images": [cto_urls
],
"makeup_output_images": [
mto_urls
],
"background_colors": [[245, 245, 245], [220, 245, 245]],
"outro_title": "Reach out to us for more information",
"address": "None",
"phone_numbers": "None",
"logo_url": "https://lvuhhlrkcuexzqtsbqyu.supabase.co/storage/v1/object/public/MagicMirror/FullImages/default.png",
"outro_video_path": f"{storename}_outro.mp4"
}
logging.info("Video Generating for {}".format(necklace_id))
video_result = generate_combined_video(**video_params)
logging.info(f"Video generation result: {video_result}")
if video_result.status != 'success':
raise Exception(f"Video generation failed: {video_result.message}")
urls = {
'video_url': video_result.video_url,
'images_url': str([result['url'] for result in image_results.nto_results])
}
logging.info("Completed combined image and video generation process")
upload_information_to_new_table(necklace_id=necklace_id,
nto_images_urls=[result['url'] for result in image_results.nto_results],
cto_images_urls=cto_urls,
mto_urls=mto_urls,
video_urls=video_result.video_url,
model_name=model_name
)
update_processed_necklaces(
necklace_id=necklace_id,
status=True,
model_name=model_name
)
except Exception as e:
raise e
logging.error(f"Error processing {necklace_id}: {str(e)}")
update_processed_necklaces(
necklace_id=necklace_id,
status=False,
model_name=model_name
)
return {
"status": "success",
}
except Exception as e:
raise e
logging.error(f"Fatal error in combined generation process: {str(e)}")
return {
'status': 'error',
'message': str(e)
}
if __name__ == "__main__":
image_url = "https://lvuhhlrkcuexzqtsbqyu.supabase.co/storage/v1/object/public/JewelmirrorModelImages/p_01.png"
storename = "ChamundiJewelsMandir"
result = combined_image_and_video_generation(image_url=image_url, storename=storename)
print(f"Process completed with status: {result}")
|