Duplicate from wenjiao/Stable-Diffusion-Side-by-Side

Co-authored-by: Wenjiao Yue <[email protected]>

.gitattributes

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README.md

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+---
+title: Stable Diffusion On Intel CPUs
+emoji: 🏢
+colorFrom: pink
+colorTo: purple
+sdk: gradio
+sdk_version: 3.15.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+duplicated_from: wenjiao/Stable-Diffusion-Side-by-Side
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import grequests
+import os
+import gradio as gr
+import numpy as np
+import random
+import torch
+import subprocess
+import time
+import json
+import base64
+from io import BytesIO
+from PIL import Image
+
+
+url = "http://54.91.63.201:80"
+
+print('=='*20)
+print(os.system("hostname -i"))
+
+def url_requests(req_list):
+    img_list = []
+    res_list = grequests.map(req_list)
+    for resp in res_list:
+        img_str = json.loads(resp.text)["img_str"]
+        print("location: ", json.loads(resp.text)["ip"])
+
+        img_byte = base64.b64decode(img_str)
+        img_io = BytesIO(img_byte)  # convert image to file-like object
+        img = Image.open(img_io)   # img is now PIL Image object
+        img_list.append(img)
+        
+    return img_list
+
+
+def img2img_generate(source_img, prompt, steps=25, strength=0.75, seed=42, guidance_scale=7.5):
+    # cpu info
+    # print(subprocess.check_output(["cat /proc/cpuinfo | grep 'model name' |uniq"], stderr=subprocess.STDOUT).decode("utf8"))
+    print('=*'*20)
+    print(type(source_img))
+    print("prompt: ", prompt)
+    buffered = BytesIO()
+    source_img.save(buffered, format="JPEG")
+    img_b64 = base64.b64encode(buffered.getvalue())
+
+    data = {"source_img": img_b64.decode(), "prompt": prompt, "steps": steps,
+            "guidance_scale": guidance_scale, "seed": seed, "strength": strength}
+
+    start_time = time.time()
+    req_list = [ 
+        grequests.post(url, data=json.dumps(data)),
+        grequests.post(url, data=json.dumps(data)),
+    ]
+    img_list = url_requests(req_list)
+    
+    return img_list
+
+
+def txt2img_generate(prompt, steps=25, seed=42, guidance_scale=7.5):
+    # cpu info
+    # print(subprocess.check_output(["cat /proc/cpuinfo | grep 'model name' |uniq"], stderr=subprocess.STDOUT).decode("utf8"))
+    print("prompt: ", prompt)
+    print("steps: ", steps)
+    data = {"prompt": prompt,
+        "steps": steps, "guidance_scale": guidance_scale, "seed": seed}
+    start_time = time.time()
+    req_list = [ 
+        grequests.post(url, data=json.dumps(data)),
+        grequests.post(url, data=json.dumps(data)),
+    ]
+    img_list = url_requests(req_list)
+
+    return img_list
+
+md = """
+This Spaces app is to demonstrate the inference of Stable Diffusion on **4th Gen Intel Xeon Scalable Processors (Sapphire Rapids)** vs. **3rd Gen Intel Xeon Scalable Processors (Ice Lake)** on Amazon Web Services. Now, you can have a try and see the significant performance speedup on 4th Gen Intel Xeon Scalable Processors!
+"""
+
+css = '''
+    .instruction{position: absolute; top: 0;right: 0;margin-top: 0px !important}
+    .arrow{position: absolute;top: 0;right: -110px;margin-top: -8px !important}
+    #component-4, #component-3, #component-10{min-height: 0}
+    .duplicate-button img{margin: 0}
+    #img_1{height:15rem}
+'''
+
+random_seed = random.randint(0, 2147483647)
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown("# Stable Diffusion Inference Demo Side-by-Side")
+    gr.Markdown(md)
+
+    with gr.Tab("Text-to-Image"):
+        with gr.Row() as text_to_image:
+            with gr.Column():
+                prompt = gr.inputs.Textbox(label='Prompt', default='a photo of an astronaut riding a horse on mars')
+                inference_steps = gr.inputs.Slider(1, 100, label='Inference Steps - increase the steps for better quality (e.g., avoiding black image) ', default=20, step=1)
+                seed = gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1)
+                guidance_scale = gr.inputs.Slider(1.0, 20.0, label='Guidance Scale - how much the prompt will influence the results', default=7.5, step=0.1)
+                txt2img_button = gr.Button("Generate Image")
+
+            with gr.Column():
+                result_image_1 = gr.Image(label="4th Gen Intel Xeon Scalable Processors (SPR)").style(height='1', rounded=True)
+                result_image_2 = gr.Image(label="3rd Gen Intel Xeon Scalable Processors (ICX)").style(height='100', rounded=False)
+
+    with gr.Tab("Image-to-Image text-guided generation"):
+        with gr.Row() as image_to_image:
+            with gr.Column():
+                source_img = gr.Image(source="upload", type="pil", value="https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg")
+                prompt_2 = gr.inputs.Textbox(label='Prompt', default='A fantasy landscape, trending on artstation')
+                inference_steps_2 = gr.inputs.Slider(1, 100, label='Inference Steps - increase the steps for better quality (e.g., avoiding black image) ', default=20, step=1)
+                seed_2 = gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1)
+                guidance_scale_2 = gr.inputs.Slider(1.0, 20.0, label='Guidance Scale - how much the prompt will influence the results', default=7.5, step=0.1)
+                strength = gr.inputs.Slider(0.0, 1.0, label='Strength - adding more noise to it the larger the strength', default=0.75, step=0.01)
+                img2img_button = gr.Button("Generate Image")
+
+            with gr.Column():
+                result_image_3 = gr.Image(label="4th Gen Intel Xeon Scalable Processors (SPR)", elem_id="img_1")
+                result_image_4 = gr.Image(label="3rd Gen Intel Xeon Scalable Processors (ICX)").style(height='24', rounded=False)
+
+    txt2img_button.click(fn=txt2img_generate, inputs=[prompt, inference_steps, seed, guidance_scale], outputs=[result_image_1, result_image_2], queue=False)
+    img2img_button.click(fn=img2img_generate, inputs=[source_img, prompt_2, inference_steps_2, strength, seed_2, guidance_scale_2], outputs=[result_image_3, result_image_4], queue=False)
+
+demo.queue(default_enabled=False).launch(debug=True)

requirements.txt

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+torch
+diffusers==0.8.1
+transformers==4.21.2
+requests
+gevent
+grequests