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import fal_client | |
import pandas as pd | |
from prompt_gen import prompt_gen | |
import requests | |
import os | |
nv_prompt_file = pd.read_excel('汉服-女词库.xlsx') | |
na_prompt_file = pd.read_excel('汉服-男词库.xlsx') | |
nv_prompt = nv_prompt_file.to_string(index=False) | |
na_prompt = na_prompt_file.to_string(index=False) | |
def cloth_gen(advice, gender): | |
lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors" | |
if gender == "男": | |
lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors" | |
else: | |
lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors" | |
prompt = prompt_gen(advice, gender) | |
prompt_start = prompt.find("Prompt") | |
if prompt_start != -1: | |
prompt = prompt[prompt_start + len("Prompt"):].strip() | |
else: | |
print("No prompt found.") | |
handler = fal_client.submit( | |
"fal-ai/fast-sdxl", | |
arguments={ | |
"prompt": prompt, | |
"negative_prompt": "face, male, female, people, person, man, woman, Multiple clothes, cartoon, illustration, animation.", | |
"image_size": "portrait_4_3", | |
"num_inference_steps": 28, | |
"guidance_scale": 7.5, | |
"num_images": 6, | |
"loras": [{"path": lora_path, "scale": 0.7}], | |
"embeddings": [], | |
"safety_checker_version": "v1", | |
"format": "jpeg" | |
}, | |
) | |
request_id = handler.request_id | |
result = fal_client.result("fal-ai/fast-sdxl", request_id) | |
cloth_image = [] | |
save_directory = "downloads" | |
image_index = 1 | |
for image in result['images']: | |
response = requests.get(image['url']) | |
if response.status_code == 200: | |
filename = os.path.join(save_directory, f"gen_cloth_{image_index}.jpeg") | |
cloth_image.append(filename) | |
with open(filename, 'wb') as f: | |
f.write(response.content) | |
image_index += 1 | |
else: | |
print(f"Failed to download image from {image['url']}") | |
return cloth_image | |
# cloth_gen() |