import fal_client import pandas as pd from prompt_gen import prompt_gen import requests import os from openai import OpenAI import random import shutil from pathlib import Path from PIL import Image 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) save_directory = "downloads" def prompt_nan(prompt): client = OpenAI() completion = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "You are a helpful assistant.", }, {"role": "user", "content": "Please showcase the overall appearance of this Hanfu robe against a contrasting white " "background. Highlight its intricate details and unique design elements, including" + prompt, } ] ) print("change prompt: ") print(completion.choices[0].message.content) return completion.choices[0].message.content def pro_gen(advice, gender, index): prompt = prompt_gen(advice, gender) start_index = prompt.find("Begin") if start_index == -1: start_index = prompt.find("begin") prompt__gen = "" if start_index != -1: start_index += len("Begin\n") end_index = prompt.find("End") if end_index != -1: prompt__gen = prompt[start_index:end_index] # if gender == "男": # prompt__gen = prompt_nan(prompt__gen) filename = os.path.join(save_directory, f"prompt_{index}.txt") with open(filename, "w") as file: file.write(prompt__gen) # print(prompt__gen) else: print("No 'promptEnd' found after 'prompt'.") else: print("No 'prompt' found in the text.") return prompt__gen def generate(lora_path, prompt__gen, index): # print(prompt__gen) handler = fal_client.submit( "fal-ai/fast-sdxl", arguments={ "prompt": prompt__gen, "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": 1, "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) image_index = index * 2 - 1 for image in result['images']: response = requests.get(image['url']) if response.status_code == 200: filename = os.path.join(save_directory, f"cloth_{image_index}.jpeg") with open(filename, 'wb') as f: f.write(response.content) image_index += 1 else: print(f"Failed to download image from {image['url']}") client = OpenAI() completion = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "You are a helpful assistant.", }, {"role": "user", "content": prompt__gen + "以上是一段对于一套汉服的描述，请根据描述内容对该套汉服进行介绍。要求以介绍的口吻输出内容", } ] ) 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") + completion.choices[ 0].message.content filename = os.path.join(save_directory, f"cloth_intro_{index * 2 - 1}.txt") with open(filename, "w") as file: file.write(cloth_intro) def convert_image_to_jpeg(input_path, output_path): try: image = Image.open(input_path) if image.mode in ('RGBA', 'LA'): image = image.convert('RGB') image.save(output_path, 'JPEG') except Exception as e: print(f"转换图像时出错: {e}") def pic_match(prompt__gen, cates, folder_path, intro_path, index): client = OpenAI() completion = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "You are a helpful assistant.", }, {"role": "user", "content": prompt__gen + "以上是关于一套汉族服饰的描述，请根据描述内容从以下几种颜色中选择最符合描述的一种，可选颜色包括：" + cates + ". 仅需输出一种颜色名称，不要带任何符号", } ] ) print(f"Selected color: {completion.choices[0].message.content}") folder_path = os.path.join(folder_path, completion.choices[0].message.content) files = os.listdir(folder_path) random_file = random.choice(files) source_file_path = os.path.join(folder_path, random_file) file_prefix, file_ext = os.path.splitext(random_file) target_file_path = os.path.join(save_directory, f"cloth_{index * 2}.jpeg") convert_image_to_jpeg(source_file_path, target_file_path) file_extension = ".txt" search_path = Path(intro_path) for file in search_path.glob(f"{file_prefix}*{file_extension}"): if file.is_file(): with open(file, "r") as f: content = f.read() client = OpenAI() completion = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "You are a helpful assistant.", }, {"role": "user", "content": content + "以上是一段对于一套汉服的描述，请根据描述内容对该套汉服进行介绍。要求以介绍的口吻输出内容", } ] ) 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") + \ completion.choices[0].message.content filename = os.path.join(save_directory, f"cloth_intro_{index * 2}.txt") with open(filename, "w") as file: file.write(cloth_intro) return target_file_path def cloth_gen(gender): cates = "Black, Blue, Green, Orange, Pink, Red, Violet, White, Yellow" lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors" folder_path = "database/female" intro_path = "database/female_intro" if gender == "男": lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors" cates = "Black, Blue, Green, Brown, Red, Violet" folder_path = "database/male" intro_path = "database/male_intro" elif gender == "女": lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors" cates = "Black, Blue, Green, Orange, Pink, Red, Violet, White, Yellow" folder_path = "database/female" intro_path = "database/female_intro" cloth_image = [] for i in range(1, 4): with open(os.path.join(save_directory, f"prompt_{i}.txt"), "r") as file: prompt__gen = file.read() generate(lora_path, prompt__gen, i) cloth_image.append(os.path.join(save_directory, f"cloth_{i*2-1}.jpeg")) pic_path = pic_match(prompt__gen, cates, folder_path, intro_path, i) cloth_image.append(pic_path) with open(os.path.join(save_directory, f"cloth_intro_1.txt"), "r") as file: cloth_intro = file.read() return cloth_image, cloth_image[0], cloth_intro