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| #!/usr/bin/env python | |
| # encoding: utf-8 | |
| import gradio as gr | |
| from datasets import load_dataset | |
| from PIL import Image | |
| import re | |
| import os | |
| import requests | |
| import threading | |
| import base64 | |
| import io | |
| sem = threading.Semaphore() | |
| def infer(prompt, negative, scale): | |
| try: | |
| url = os.environ.get('SERVICE_URL', 'https://modelbest.cn/') | |
| sem.acquire() | |
| resp = requests.post(url, headers={ | |
| "X-Model-Best-Model": "viscpm-paint-balance", | |
| "X-Model-Best-Trace-ID": "test-trace", | |
| }, json={ | |
| "question": prompt, | |
| "negative_prompt": negative, | |
| "num_images_per_prompt": 4, | |
| }) | |
| sem.release() | |
| resp = resp.json() | |
| images = resp['data']['response'] | |
| images = [Image.open(io.BytesIO(base64.b64decode(encoded_image))).convert("RGB") for encoded_image in images] | |
| return images | |
| except Exception as e: | |
| print(e) | |
| return [] | |
| with gr.Blocks() as demo: | |
| gr.Markdown('<div align="center"><big><b>百亿参数量中英双语多模态大模型VisCPM</b></big></div>') | |
| with gr.Column(variant="panel"): | |
| with gr.Row(variant="compact"): | |
| with gr.Column(variant="compact"): | |
| text = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="输入提示词", | |
| ).style( | |
| container=False, | |
| ) | |
| neg_text = gr.Textbox( | |
| label="Enter your negative prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="输入负向提示词（你不想生成的内容）", | |
| ).style( | |
| container=False, | |
| ) | |
| btn = gr.Button("生成图像").style(full_width=False) | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery", height="1024" | |
| ).style(columns=[2], rows=[2], object_fit="contain") | |
| btn.click(infer, [text, neg_text], gallery) | |
| if __name__ == "__main__": | |
| demo.launch() |