176 lines
7.6 KiB
Python
176 lines
7.6 KiB
Python
import os
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import base64
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from datetime import datetime
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import requests
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# 全局配置：请在此处填入你的 DashScope API Key
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API_KEY = "sk-26818d3a4eb14b41a71f4d0319e4edfa" # <-- 在此处粘贴你的 API Key
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BASE_URL = "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
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MODEL = "qwen-image-plus"
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def generate_qwen_image(prompt: str, *, size: str = "1328*1328") -> str:
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"""调用 DashScope 原生接口生成图片，返回 base64 字符串。
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入参:
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prompt: 生成图片的提示词
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size: 图片尺寸，形如 "宽*高"（例如 "1328*1328"）
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返回:
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base64 字符串（不带 data: 前缀），可自行解码保存为图片
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"""
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if not API_KEY:
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raise RuntimeError("请先在代码顶部设置 API_KEY")
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {API_KEY}",
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}
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payload = {
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"model": MODEL,
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"input": {
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"messages": [
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{
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"role": "user",
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"content": [
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{"text": prompt}
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],
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}
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]
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},
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"parameters": {
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"negative_prompt": "",
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"prompt_extend": True,
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"watermark": True,
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"size": size,
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},
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}
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r = requests.post(BASE_URL, headers=headers, json=payload, timeout=120)
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r.raise_for_status()
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data = r.json()
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def extract_image_from_content(content_list):
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"""从 content 列表中提取图片，优先 URL 后 base64"""
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for item in content_list:
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if not isinstance(item, dict):
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continue
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# 尝试提取 URL
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url = item.get("image") or item.get("image_url") or item.get("url")
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if isinstance(url, str) and url.startswith("http"):
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img_bytes = requests.get(url, timeout=120).content
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return base64.b64encode(img_bytes).decode("utf-8")
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# 尝试提取 base64
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b64 = item.get("b64") or item.get("b64_json") or item.get("image_base64")
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if isinstance(b64, str) and len(b64) > 100:
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return b64
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return None
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output = data.get("output", {})
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# 尝试路径1：output.choices[0].message.content[*]
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choices = output.get("choices", [])
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if choices:
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content_list = choices[0].get("message", {}).get("content", [])
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result = extract_image_from_content(content_list)
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if result:
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return result
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# 尝试路径2：output.results[0].content[*]
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results = output.get("results", [])
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if results:
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content_list = results[0].get("content", [])
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result = extract_image_from_content(content_list)
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if result:
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return result
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raise RuntimeError("未获得图片结果")
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def save_generated_image(query: str, folder: str = "tools/img_gen/tmp/raw") -> str:
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"""根据查询生成图片并保存到 result 目录。
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入参:
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query: 图片生成的提示词
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返回:
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保存的图片文件路径
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"""
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b64 = generate_qwen_image(query)
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img_bytes = base64.b64decode(b64)
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result_dir = folder
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os.makedirs(result_dir, exist_ok=True)
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filename = datetime.now().strftime("%Y%m%d_%H%M%S") + ".png"
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out_path = os.path.join(result_dir, filename)
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with open(out_path, "wb") as f:
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f.write(img_bytes)
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print(f"图片已保存: {out_path}")
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return out_path
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if __name__ == "__main__":
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female_prompt_base = "一个好看的仙侠女性头像。只有头部和面部。二次元风格的漫画图片，略微Q版，正面看镜头。纯白背景。像素风格，细节别太多。"
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female_affixes = [
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"紫色长发，表情嗔怒，带有一丝冷峻，有一个簪子。",
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"乌黑直发，眉心一点红砂，清冷淡漠，镶玉步摇。",
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"银白短发，英气微笑，发梢轻卷，耳坠为小灵铃。",
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"墨绿长发，高马尾，目光坚毅，额前碎发，佩青竹簪。",
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"渐变粉蓝长卷发，眸有星点，温柔含笑，薄纱额饰。",
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"赤红披发，英气冷艳，眉尾上挑，凤羽发冠。",
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"浅金长发，缎带系发，气质圣洁，流苏步摇。",
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"乌青长发，微皱眉，眼尾红妆，一枚冰晶发卡。",
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"白发如雪，神情淡然，眉心月印，玉质头箍。",
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"靛蓝长发，俏皮眨眼，脸颊淡粉，葫芦小发簪。",
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"茶棕双丸子头，活泼微笑，脸上淡淡雀斑，小葵花发卡。",
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"青丝长发半披半挽，清雅端庄，蝶形玉簪。",
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"淡紫短波浪发，俏皮吐舌，星月耳饰。",
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"墨发低侧马尾，冷静专注，细链额饰垂坠。",
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"湖绿挑染长发，狡黠微笑，狐耳发饰点缀。",
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"灰蓝长直发，平刘海，面无表情，银环头饰。",
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]
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male_prompt_base = "一个英俊的的仙侠男性头像。只有头部和面部。二次元风格的漫画图片，略微Q版，正面看镜头。纯白背景。像素风格，细节别太多。"
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male_affixes = [
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"乌发高束，剑眉星目，气质冷峻，青玉发冠。",
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"银白长发，淡笑从容，额间玄纹，流苏头箍。",
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"墨发披肩，脸上一抹浅疤，坚毅沉稳，黑金发簪。",
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"深棕短发，目光凌厉，薄唇紧抿，皮绳束发。",
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"蓝黑长发，发尾微卷，温润如玉，白玉簪。",
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"赤褐长发，桀骜挑眉，轻笑不羁，耳坠小铜铃。",
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"玄青半束发，沉静内敛，额前碎发，银纹额饰。",
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"白发如雪，清隽淡笑，眉心一点冰蓝印，细环头饰。",
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"墨发高马尾，目如寒星，英气逼人，羽纹发冠。",
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"亚麻色短发，随性浅笑，轻胡茬，细革头环。",
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"乌青长发，神情冷淡，眼神专注，剑形耳坠。",
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"银灰长直发，肃杀气质，额缠黑带，简洁利落。",
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"深紫挑染长发，狡黠微笑，眸底流光，狐尾发饰。",
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"墨发半披，眼神温和从容，玉串发夹。",
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"金棕长发，爽朗大笑，额前碎发，兽牙发簪。",
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"青黑短发，专注坚定，线条硬朗，细链发饰垂坠。",
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]
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sect_prompt_base = "像素化的仙侠宗门场景图片，极度像素化，颗粒感强，线条轮廓粗，极简主义，二次元风格漫画图片。"
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sect_affixes = [
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"山巅飘渺云海，云纹禁制光芒环绕，远处群峰。",
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"灵兽栖地，兽栏密布，岩石兽穴。",
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"湖面倒影，中央悬浮巨大水镜，镜面波光粼粼，雾气弥漫。",
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"幽冥宗门，阴暗昏沉，黑雾弥漫，冷厉气息，幽蓝鬼火点点。",
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"炼器工坊，机关密布，熔炉火光。",
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"合欢宫殿，粉红雾气，花瓣飘舞，柔和光晕，纱幔轻垂。",
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"镇魂大殿，铁血肃杀，封印符文，镇压法阵，黑铁锁链。",
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"幽影之地，暗影重重，光影交错，幽冥之气，黑雾吞噬轮廓。",
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"船帆如云，炼器炉火。",
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]
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# for affix in male_affixes:
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# prompt_text = male_prompt_base + affix
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# save_generated_image(prompt_text, folder="tools/img_gen/tmp/males")
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# for affix in female_affixes:
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# prompt_text = female_prompt_base + affix
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# save_generated_image(prompt_text, folder="tools/img_gen/tmp/females")
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for i, affix in enumerate(sect_affixes):
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prompt_text = sect_prompt_base + affix
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save_generated_image(prompt_text, folder="tools/img_gen/tmp/sects") |