init commit

README.md

@@ -1,5 +1,5 @@
 ---
-title: Taiyi Stable Diffusion 1B Chinese
+title: Taiyi Stable Diffusion Chinese
 emoji: 💩
 colorFrom: red
 colorTo: red

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+import torch
+from PIL import Image
+import numpy as np
+from io import BytesIO
+from diffusers import StableDiffusionImg2ImgPipeline, StableDiffusionPipeline, UNet2DConditionModel, AutoencoderKL
+from transformers import BertTokenizer, BertModel
+
+
+device="cuda"
+model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1"
+
+# pipe_img2img = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, unet=unet).to(device)
+pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id).to(device)
+
+def resize(w_val,l_val,img):
+  img = Image.open(img)
+  img = img.resize((w_val,l_val), Image.Resampling.LANCZOS)
+  return img
+
+
+def infer(prompt, guide, steps, width, height): 
+    image_list = pipe_text2img([prompt], guidance_scale=guide, num_inference_steps=steps, width=width, height=height)
+    images = []
+    for i, image in enumerate(image_list["sample"]):
+        images.append(image)    
+    return image
+
+gr.Interface(fn=infer, inputs=
+    [
+        # gr.Image(source="upload", type="filepath", label="原始图像"), 
+        gr.Textbox(label = '提示词(prompt)'),
+        gr.Slider(2, 15, value = 7, label = '文本引导强度'),
+        gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数'),
+        gr.Slider(256, 768, value = 512, step = 64, label = '宽度'),
+        gr.Slider(256, 768, value = 512, step = 64, label = '高度'),
+    ],outputs='image').queue(max_size=10).launch(enable_queue=True)