Duplicate from IDEA-CCNL/Taiyi-Stable-Diffusion-Chinese

Co-authored-by: weifeng <wf-genius@users.noreply.huggingface.co>

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README.md

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+---
+title: Taiyi Stable Diffusion Chinese
+emoji: 🤯
+colorFrom: red
+colorTo: red
+sdk: gradio
+sdk_version: 3.10.0
+app_file: app.py
+pinned: false
+license: creativeml-openrail-m
+duplicated_from: IDEA-CCNL/Taiyi-Stable-Diffusion-Chinese
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from PIL import Image
+import torch
+
+from diffusers import (
+    StableDiffusionPipeline,
+    StableDiffusionImg2ImgPipeline,
+    StableDiffusionInpaintPipeline,
+)
+
+device="cuda"
+model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1"
+
+pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(device)
+pipe_img2img = StableDiffusionImg2ImgPipeline(**pipe_text2img.components).to(device)
+
+
+# pipe_inpaint = StableDiffusionInpaintPipeline.from_pretrained(model_id).to(device)    # work
+# pipe_inpaint = StableDiffusionInpaintPipeline(**pipe_text2img.components)   # not work
+# def infer_text2img(prompt, guide, steps, width, height): 
+#     output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps,)
+#     image = output.images[0]
+#     return image
+
+def infer_text2img(prompt, guide, steps, width, height, image_in, strength):
+    if image_in is not None:
+        init_image = image_in.convert("RGB").resize((width, height))
+        output = pipe_img2img(prompt, image=init_image, strength=strength, guidance_scale=guide, num_inference_steps=steps)
+    else:
+        output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps,)
+    image = output.images[0]
+    return image
+
+def infer_inpaint(prompt, guide, steps, width, height, image_in): 
+    init_image = image_in["image"].convert("RGB").resize((width, height))
+    mask = image_in["mask"].convert("RGB").resize((width, height))
+
+    output = pipe_inpaint(prompt, \
+                        init_image=init_image, mask_image=mask, \
+                        width=width, height=height, \
+                        guidance_scale=7.5, num_inference_steps=20)
+    image = output.images[0]
+    return image
+
+with gr.Blocks() as demo:
+    examples = [
+                ["飞流直下三千尺, 疑是银河落九天, 瀑布, 插画"], 
+                ["东临碣石, 以观沧海, 波涛汹涌, 插画"], 
+                ["孤帆远影碧空尽，惟见长江天际流,油画"],
+                ["女孩背影, 日落, 唯美插画"],
+                ]
+    with gr.Row():
+        with gr.Column(scale=1, ):
+            image_out = gr.Image(label = '输出(output)')
+        with gr.Column(scale=1, ):
+            image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图（非必须）(ref)")
+            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, step = 0.1, label = '文本引导强度(guidance scale)')
+                steps = gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)')
+                width = gr.Slider(384, 640, value = 512, step = 64, label = '宽度(width)')
+                height = gr.Slider(384, 640, value = 512, step = 64, label = '高度(height)')
+                strength = gr.Slider(0, 1.0, value = 0.8, step = 0.02, label = '参考图改变程度(strength)')
+                ex = gr.Examples(examples, fn=infer_text2img, inputs=[prompt, guide, steps, width, height], outputs=image_out)
+
+        # with gr.Column(scale=1, ):
+        #     image_in = gr.Image(source='upload', tool='sketch', elem_id="image_upload", type="pil", label="Upload")
+        #     inpaint_prompt = gr.Textbox(label = '提示词(prompt)')
+        #     inpaint_btn = gr.Button("图像编辑(Inpaint)")
+            # img2img_prompt = gr.Textbox(label = '提示词(prompt)')
+            # img2img_btn = gr.Button("图像编辑(Inpaint)")
+        submit_btn.click(fn = infer_text2img, inputs = [prompt, guide, steps, width, height, image_in, strength], outputs = image_out)
+        # inpaint_btn.click(fn = infer_inpaint, inputs = [inpaint_prompt, width, height, image_in], outputs = image_out)
+        # img2img_btn.click(fn = infer_img2img, inputs = [img2img_prompt, width, height, image_in], outputs = image_out)
+demo.queue(concurrency_count=1, max_size=8).launch()

requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cu113 
+torch
+torchvision
+git+https://github.com/huggingface/diffusers.git
+transformers
+accelerate