Update app.py

app.py

@@ -0,0 +1,236 @@
+import gradio as gr
+
+model_ids = {"models/runwayml/stable-diffusion-v1-5":"stable-diffusion-v1-5",
+           "models/stabilityai/stable-diffusion-2":"stable-diffusion-2",
+           "models/prompthero/openjourney":"openjourney",
+           }
+tab_actions = []
+tab_titles = []
+for model_id in model_ids.keys():
+    print(model_id, model_ids[model_id])
+    try:
+        tab = gr.Interface.load(model_id)
+        tab_actions.append(tab)
+        tab_titles.append(model_ids[model_id])
+    except:
+        pass
+
+def infer(prompt):
+    # gr.Interface.load("models/runwayml/stable-diffusion-v1-5",prompt=prompt).launch()
+    return prompt
+
+start_work = """async() => {
+    function isMobile() {
+        try {
+            document.createEvent("TouchEvent"); return true;
+        } catch(e) {
+            return false; 
+        }
+    }
+
+	function getClientHeight()
+	{
+	  var clientHeight=0;
+	  if(document.body.clientHeight&&document.documentElement.clientHeight) {
+		var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
+	  } else {
+		var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
+	  }
+	  return clientHeight;
+	}
+ 
+    function setNativeValue(element, value) {
+      const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set;
+      const prototype = Object.getPrototypeOf(element);
+      const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set;
+      
+      if (valueSetter && valueSetter !== prototypeValueSetter) {
+            prototypeValueSetter.call(element, value);
+      } else {
+            valueSetter.call(element, value);
+      }
+    }
+
+    var gradioEl = document.querySelector('body > gradio-app').shadowRoot;
+    if (!gradioEl) {
+        gradioEl = document.querySelector('body > gradio-app');
+    }
+    
+    if (typeof window['gradioEl'] === 'undefined') {
+        window['gradioEl'] = gradioEl;
+        
+        tabitems = window['gradioEl'].querySelectorAll('.tabitem');
+        for (var i = 0; i < tabitems.length; i++) {    
+            tabitems[i].childNodes[0].children[0].style.display='none';
+            tabitems[i].childNodes[0].children[1].children[0].style.display='none';
+            tabitems[i].childNodes[0].children[1].children[1].children[0].children[1].style.display="none"; 
+        }    
+        tab_demo = window['gradioEl'].querySelectorAll('#tab_demo')[0];
+        tab_demo.style.display = "block";
+        tab_demo.setAttribute('style', 'height: 100%;');
+
+        const page1 = window['gradioEl'].querySelectorAll('#page_1')[0];
+        const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; 
+    
+        page1.style.display = "none";
+        page2.style.display = "block";    
+
+        window['prevPrompt'] = '';
+        window['doCheckPrompt'] = 0;
+        window['checkPrompt'] = function checkPrompt() {
+            try {
+                    texts = window['gradioEl'].querySelectorAll('textarea');
+                    text0 = texts[0];    
+                    text1 = texts[1];
+                    if (window['doCheckPrompt'] == 0 && window['prevPrompt'] != text1.value) {
+                            window['doCheckPrompt'] = 1;
+                            window['prevPrompt'] = text1.value;
+                            for (var i = 2; i < texts.length; i++) {
+                                setNativeValue(texts[i], text1.value);
+                                texts[i].dispatchEvent(new Event('input', { bubbles: true }));
+                            }                        
+                            setTimeout(function() {
+                                text1 = window['gradioEl'].querySelectorAll('textarea')[1];    
+                                //console.log('do_click()_1_' + text1.value);
+                                
+                                btns = window['gradioEl'].querySelectorAll('button');
+                                for (var i = 0; i < btns.length; i++) {
+                                    if (btns[i].innerText == 'Submit') {
+                                        btns[i].focus();
+                                        btns[i].click();                
+                                       //break;
+                                    }
+                                }
+                                //console.log('do_click()_3_');
+                                window['doCheckPrompt'] = 0;
+                            }, 10);                   
+                    }
+            } catch(e) {
+            }        
+        }
+        window['checkPrompt_interval'] = window.setInterval("window.checkPrompt()", 100);         
+    }
+
+    /*
+    texts = gradioEl.querySelectorAll('textarea');
+    text0 = gradioEl.querySelectorAll('textarea')[0];    
+    text1 = gradioEl.querySelectorAll('textarea')[0];
+    
+    for (var i = 1; i < texts.length; i++) {
+        setNativeValue(texts[i], text0.value);
+        texts[i].dispatchEvent(new Event('input', { bubbles: true }));
+    }
+
+    var st = setTimeout(function() {
+        text1 = window['gradioEl'].querySelectorAll('textarea')[1];    
+        console.log('do_click()_1_' + text1.value);
+        
+        btns = window['gradioEl'].querySelectorAll('button');
+        for (var i = 0; i < btns.length; i++) {
+            if (btns[i].innerText == 'Submit') {
+                btns[i].focus();
+                btns[i].click();                
+               //break;
+            }
+        }
+        console.log('do_click()_3_');
+    }, 10);
+    */
+    
+    return false;
+}"""
+
+with gr.Blocks(title='Text to Image') as demo:
+    with gr.Group(elem_id="page_1", visible=True) as page_1:
+        with gr.Box():            
+            with gr.Row():
+                start_button = gr.Button("Let's GO!", elem_id="start-btn", visible=True) 
+                start_button.click(fn=None, inputs=[], outputs=[], _js=start_work)
+                
+    with gr.Group(elem_id="page_2", visible=False) as page_2:                 
+            with gr.Row(elem_id="prompt_row"):
+                prompt_input0 = gr.Textbox(lines=4, label="prompt")
+                prompt_input1 = gr.Textbox(lines=4, label="prompt", visible=False)
+            with gr.Row():
+                submit_btn = gr.Button(value = "submit",elem_id="erase-btn").style(
+                        margin=True,
+                        rounded=(True, True, True, True),
+                    )
+            with gr.Row(elem_id='tab_demo', visible=True).style(height=5):
+                tab_demo = gr.TabbedInterface(tab_actions, tab_titles) 
+
+            submit_btn.click(fn=infer, inputs=[prompt_input0], outputs=[prompt_input1])
+
+# prompt_input = gr.Textbox(lines=4, label="Input prompt")
+# tab_demo = gr.TabbedInterface([sd15_demo, sd20_demo, openjourney_demo], ["stable-diffusion-v1-5", "stable-diffusion-2", "openjourney"])
+
+# demo = gr.Interface(fn=infer, 
+#                      inputs=[prompt_input], 
+#                      outputs=[tab_demo],
+#                     )
+
+if __name__ == "__main__":
+    demo.launch()
+
+    
+
+# import os
+# os.environ['CUDA_LAUNCH_BLOCKING'] = "1"
+# from diffusers import StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, StableDiffusionInpaintPipeline, StableDiffusionInpaintPipelineLegacy
+
+# import gradio as gr
+# import PIL.Image
+# import numpy as np
+# import random
+# import torch
+# import subprocess
+
+# device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+# # print('Using device:', device)
+
+# HF_TOKEN_SD=os.environ.get('HF_TOKEN_SD')
+
+# if 0==0:
+#     model_id = "runwayml/stable-diffusion-v1-5"
+
+#     model_id = "prompthero/openjourney" 
+    
+#     # pipeClass = StableDiffusionImg2ImgPipeline
+#     pipeClass = StableDiffusionPipeline     
+#     className = pipeClass.__name__
+#     if className == 'StableDiffusionInpaintPipeline':
+#         model_id = "runwayml/stable-diffusion-inpainting"    
+        
+#     sd_pipe = pipeClass.from_pretrained(
+#         model_id, 
+#         # revision="fp16",
+#         torch_dtype=torch.float16, 
+#         # use_auth_token=HF_TOKEN_SD
+#       ) # .to(device)
+
+# def predict(prompt, steps=100, seed=42, guidance_scale=6.0):
+#     #torch.cuda.empty_cache()
+#     # print(subprocess.check_output(["nvidia-smi"], stderr=subprocess.STDOUT).decode("utf8"))
+#     generator = torch.manual_seed(seed)
+#     images = sd_pipe([prompt], 
+#             generator=generator, 
+#             num_inference_steps=steps, 
+#             eta=0.3, 
+#             guidance_scale=guidance_scale)["sample"]
+#     # print(subprocess.check_output(["nvidia-smi"], stderr=subprocess.STDOUT).decode("utf8"))
+#     return images[0]
+
+# random_seed = random.randint(0, 2147483647)
+# gr.Interface(
+#     predict,
+#     inputs=[
+#         gr.inputs.Textbox(label='Prompt', default='a chalk pastel drawing of a llama wearing a wizard hat'),
+#         gr.inputs.Slider(1, 100, label='Inference Steps', default=50, step=1),
+#         gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1),
+#         gr.inputs.Slider(1.0, 20.0, label='Guidance Scale - how much the prompt will influence the results', default=6.0, step=0.1),
+#     ],
+#     outputs=gr.Image(shape=[256,256], type="pil", elem_id="output_image"),
+#     css="#output_image{width: 256px}",
+#     title="Text-to-Image_Latent_Diffusion",
+#     # description="This Spaces contains a text-to-image Latent Diffusion process for the <a href=\"https://huggingface.co/CompVis/ldm-text2im-large-256\">ldm-text2im-large-256</a> model by <a href=\"https://huggingface.co/CompVis\">CompVis</a> using the <a href=\"https://github.com/huggingface/diffusers\">diffusers library</a>. The goal of this demo is to showcase the diffusers library and you can check how the code works here. If you want the state-of-the-art experience with Latent Diffusion text-to-image check out the <a href=\"https://huggingface.co/spaces/multimodalart/latentdiffusion\">main Spaces</a>.",
+# ).launch()