Spaces:
Sleeping
Sleeping
| 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/NA.safetensors" | |
| if gender == "男": | |
| lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors" | |
| elif gender == "女": | |
| lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors" | |
| prompt = prompt_gen(advice, gender) | |
| start_index = prompt.find("prompt" or "Prompt") | |
| intro_index = prompt.find("服饰风格介绍") | |
| cloth_intro = "" | |
| promptGen = "" | |
| if start_index != -1: | |
| start_index += len("prompt\n") | |
| end_index = prompt.find("promptEnd") | |
| if end_index != -1: | |
| extracted_content = prompt[start_index:end_index] | |
| promptGen = extracted_content | |
| print(extracted_content) | |
| else: | |
| print("No 'promptEnd' found after 'prompt'.") | |
| else: | |
| print("No 'prompt' found in the text.") | |
| if intro_index != -1: | |
| intro_index += len("服饰风格介绍\n") | |
| cloth_intro = ("汉服，是汉民族的传统服饰。又称衣冠、衣裳、汉装。汉服是中国“衣冠上国”“礼仪之邦”“锦绣中华”的体现，承载了中国的染织绣等杰出" | |
| "工艺和美学，传承了30多项中国非物质文化遗产以及受保护的中国工艺美术。\n") + prompt[intro_index:] | |
| print(cloth_intro) | |
| else: | |
| print("No '服饰风格介绍' found.") | |
| handler = fal_client.submit( | |
| "fal-ai/fast-sdxl", | |
| arguments={ | |
| "prompt": promptGen, | |
| "negative_prompt": "human, people, person, man, woman, child, model, face, head, eyes, hands, arms, legs, " | |
| "feet, hair, portrait, worst quality, low quality, normal quality, lowres, signature, " | |
| "watermark, jpeg artifacts, logo, monochrome, grayscale, ugly", | |
| "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_image[0], cloth_intro | |