3x3

README copy.md

@@ -1,13 +0,0 @@
----
-title: Pai Diffusion Large Zh
-emoji: 📚
-colorFrom: yellow
-colorTo: green
-sdk: gradio
-sdk_version: 3.11.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 from LdmZhPipeline import LDMZhTextToImagePipeline
 import torch
+import numpy as np
+from PIL import Image
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model_id = "alibaba-pai/pai-diffusion-poem-large-zh"
@@ -9,9 +11,16 @@ pipe_text2img = LDMZhTextToImagePipeline.from_pretrained(model_id, use_auth_toke
 pipe_text2img = pipe_text2img.to(device)
 
 def infer_text2img(prompt, guide, steps):
-    output = pipe_text2img(prompt, guidance_scale=guide, num_inference_steps=steps, use_sr=True)
-    image = output.images[0]
-    return image
+    output = pipe_text2img([prompt]*9, guidance_scale=guide, num_inference_steps=steps)
+    images = output.images
+    images = [np.array(images[i]) for i in range(9)]
+    images = np.concatenate([
+        np.concatenate(images[0:3], axis=0),
+        np.concatenate(images[3:6], axis=0),
+        np.concatenate(images[6:9], axis=0),
+    ], axis=1)
+    images = Image.fromarray(images)
+    return images
 
 with gr.Blocks() as demo:
     examples = [
@@ -21,9 +30,9 @@ with gr.Blocks() as demo:
                 ]
     with gr.Row():
         with gr.Column(scale=1, ):
-            image_out = gr.Image(label = '输出(Output)')
+            image_out = gr.Image(label = '输出(output)')
         with gr.Column(scale=1, ):
-            prompt = gr.Textbox(label = '提示词(Prompt)')
+            prompt = gr.Textbox(label = '提示词(prompt)')
             submit_btn = gr.Button("生成图像(Generate)")
             with gr.Row(scale=0.5 ):
                 guide = gr.Slider(2, 15, value = 7, label = '文本引导强度(guidance scale)')