Update app.py

app.py

@@ -1,7 +1,8 @@
 from transformers import pipeline
 import gradio as gr
 import random
-import paddlehub as hub
+import string
+import paddlehub as hub 
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from loguru import logger
@@ -23,23 +24,6 @@ def getTextTrans(text, source='zh', target='en'):
     except Exception as e:
         return text 
         
-extend_prompt_pipe = pipeline('text-generation', model='yizhangliu/prompt-extend', max_length=77, pad_token_id=0)
-
-def load_prompter():
-  prompter_model = AutoModelForCausalLM.from_pretrained("microsoft/Promptist")
-  tokenizer = AutoTokenizer.from_pretrained("gpt2")
-  tokenizer.pad_token = tokenizer.eos_token
-  tokenizer.padding_side = "left"
-  return prompter_model, tokenizer
-prompter_model, prompter_tokenizer = load_prompter()
-def extend_prompt_microsoft(in_text):
-    input_ids = prompter_tokenizer(in_text.strip()+" Rephrase:", return_tensors="pt").input_ids
-    eos_id = prompter_tokenizer.eos_token_id
-    outputs = prompter_model.generate(input_ids, do_sample=False, max_new_tokens=75, num_beams=8, num_return_sequences=8, eos_token_id=eos_id, pad_token_id=eos_id, length_penalty=-1.0)
-    output_texts = prompter_tokenizer.batch_decode(outputs, skip_special_tokens=True)
-    res = output_texts[0].replace(in_text+" Rephrase:", "").strip()
-    return res
-    
 space_ids = {
             "spaces/stabilityai/stable-diffusion": "SD 2.1",
             "spaces/runwayml/stable-diffusion-v1-5": "SD 1.5",
@@ -50,9 +34,56 @@ space_ids = {
 tab_actions = []
 tab_titles = []
 
+extend_prompt_1 = True
+extend_prompt_2 = True
+extend_prompt_3 = True
+
 thanks_info = "Thanks: "
-thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/daspartho/prompt-extend' _blank><font style='color:blue;weight:bold;'>prompt-extend</font></a>]"
-thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/microsoft/Promptist' _blank><font style='color:blue;weight:bold;'>Promptist</font></a>]"
+if extend_prompt_1:
+    extend_prompt_pipe = pipeline('text-generation', model='yizhangliu/prompt-extend', max_length=77, pad_token_id=0)
+    thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/daspartho/prompt-extend' _blank><font style='color:blue;weight:bold;'>prompt-extend(1)</font></a>]"
+if extend_prompt_2:
+    def load_prompter():
+      prompter_model = AutoModelForCausalLM.from_pretrained("microsoft/Promptist")
+      tokenizer = AutoTokenizer.from_pretrained("gpt2")
+      tokenizer.pad_token = tokenizer.eos_token
+      tokenizer.padding_side = "left"
+      return prompter_model, tokenizer
+    prompter_model, prompter_tokenizer = load_prompter()
+    def extend_prompt_microsoft(in_text):
+        input_ids = prompter_tokenizer(in_text.strip()+" Rephrase:", return_tensors="pt").input_ids
+        eos_id = prompter_tokenizer.eos_token_id 
+        outputs = prompter_model.generate(input_ids, do_sample=False, max_new_tokens=75, num_beams=8, num_return_sequences=8, eos_token_id=eos_id, pad_token_id=eos_id, length_penalty=-1.0)
+        output_texts = prompter_tokenizer.batch_decode(outputs, skip_special_tokens=True)
+        res = output_texts[0].replace(in_text+" Rephrase:", "").strip()
+        return res    
+    thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/microsoft/Promptist' _blank><font style='color:blue;weight:bold;'>Promptist(2)</font></a>]"
+if extend_prompt_3:
+    MagicPrompt = gr.Interface.load("spaces/Gustavosta/MagicPrompt-Stable-Diffusion")
+    thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/spaces/Gustavosta/MagicPrompt-Stable-Diffusion' _blank><font style='color:blue;weight:bold;'>MagicPrompt(3)</font></a>]"
+
+do_dreamlike_photoreal = True
+if do_dreamlike_photoreal:
+    def add_random_noise(prompt, noise_level=0.1):
+        # Get the percentage of characters to add as noise
+        percentage_noise = noise_level * 5
+        # Get the number of characters to add as noise
+        num_noise_chars = int(len(prompt) * (percentage_noise/100))
+        # Get the indices of the characters to add noise to
+        noise_indices = random.sample(range(len(prompt)), num_noise_chars)
+        # Add noise to the selected characters
+        prompt_list = list(prompt)
+        for index in noise_indices:
+            prompt_list[index] = random.choice(string.ascii_letters + string.punctuation)
+        new_prompt = "".join(prompt_list)
+        return new_prompt
+        
+    dreamlike_photoreal_2_0 = gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-2.0")
+    dreamlike_image = gr.Image(label="Dreamlike Photoreal 2.0")
+
+    tab_actions.append(dreamlike_image)
+    tab_titles.append("Dreamlike_2.0")
+    thanks_info += "[<a style='display:inline-block' href='https://huggingface.co/models/dreamlike-art/dreamlike-photoreal-2.0' _blank><font style='color:blue;weight:bold;'>dreamlike-photoreal-2.0</font></a>]"
 
 for space_id in space_ids.keys():
     print(space_id, space_ids[space_id])
@@ -94,6 +125,8 @@ start_work = """async() => {
             valueSetter.call(element, value);
       }
     }
+    window['tab_advanced'] = 0;
+    
     var gradioEl = document.querySelector('body > gradio-app').shadowRoot;
     if (!gradioEl) {
         gradioEl = document.querySelector('body > gradio-app');
@@ -103,7 +136,6 @@ start_work = """async() => {
         window['gradioEl'] = gradioEl;
         tabitems = window['gradioEl'].querySelectorAll('.tabitem');
         tabitems_title = window['gradioEl'].querySelectorAll('#tab_demo')[0].children[0].children[0].children;
-        
         for (var i = 0; i < tabitems.length; i++) {   
             if (tabitems_title[i].innerText.indexOf('SD') >= 0) {
                 tabitems[i].childNodes[0].children[0].style.display='none';
@@ -113,9 +145,11 @@ start_work = """async() => {
                     }
                 }
             } else if (tabitems_title[i].innerText.indexOf('Taiyi') >= 0) {
-                tabitems[3].children[0].children[0].children[1].style.display='none';
+                tabitems[i].children[0].children[0].children[1].style.display='none';
                 tabitems[i].children[0].children[0].children[0].children[0].children[1].style.display='none';
-            }            
+            } else if (tabitems_title[i].innerText.indexOf('Dreamlike') >= 0) {
+                tabitems[i].childNodes[0].children[0].children[1].style.display='none';
+            }
         }  
         
         tab_demo = window['gradioEl'].querySelectorAll('#tab_demo')[0];
@@ -124,17 +158,27 @@ start_work = """async() => {
         const page1 = window['gradioEl'].querySelectorAll('#page_1')[0];
         const page2 = window['gradioEl'].querySelectorAll('#page_2')[0];
         
-        btns_1 = window['gradioEl'].querySelector('#input_col1_row2').children;
+        btns_1 = window['gradioEl'].querySelector('#input_col1_row3').children;
         btns_1_split = 100 / btns_1.length;
         for (var i = 0; i < btns_1.length; i++) {
             btns_1[i].setAttribute('style', 'min-width:0px;width:' + btns_1_split + '%;');
         }
         page1.style.display = "none";
-        page2.style.display = "block";    
+        page2.style.display = "block";  
+        prompt_work = window['gradioEl'].querySelectorAll('#prompt_work');
+        for (var i = 0; i < prompt_work.length; i++) {
+            prompt_work[i].style.display='none';
+        }         
+        
         window['prevPrompt'] = '';
         window['doCheckPrompt'] = 0;
         window['checkPrompt'] = function checkPrompt() {
             try {
+                    prompt_work = window['gradioEl'].querySelectorAll('#prompt_work');
+                    if (prompt_work.length > 0 && prompt_work[0].children.length > 1) {
+                        prompt_work[0].children[1].style.display='none';
+                        prompt_work[0].style.display='block';
+                    }            
                     text_value = window['gradioEl'].querySelectorAll('#prompt_work')[0].querySelectorAll('textarea')[0].value;
                     progress_bar = window['gradioEl'].querySelectorAll('.progress-bar');
                     if (window['doCheckPrompt'] === 0 && window['prevPrompt'] !== text_value && progress_bar.length == 0) {
@@ -176,18 +220,43 @@ start_work = """async() => {
     return false;
 }"""
 
+switch_tab_advanced = """async() => {
+    window['tab_advanced'] = 1 - window['tab_advanced'];
+    if (window['tab_advanced']==0) {
+        action = 'none';
+    } else {
+        action = 'block';
+    }
+    tabitems = window['gradioEl'].querySelectorAll('.tabitem');
+    tabitems_title = window['gradioEl'].querySelectorAll('#tab_demo')[0].children[0].children[0].children;  
+    for (var i = 0; i < tabitems.length; i++) {   
+        if (tabitems_title[i].innerText.indexOf('SD') >= 0) {
+            for (var j = 0; j < tabitems[i].childNodes[0].children[1].children.length; j++) {
+                if (j != 1) {
+                    tabitems[i].childNodes[0].children[1].children[j].style.display=action;
+                }
+            }
+        } else if (tabitems_title[i].innerText.indexOf('Taiyi') >= 0) {
+            tabitems[i].children[0].children[0].children[1].style.display=action;
+        }
+    }
+    return false;
+}"""
+
 def prompt_extend(prompt, PM):    
     prompt_en = getTextTrans(prompt, source='zh', target='en')
     if PM == 1:
         extend_prompt_en = extend_prompt_pipe(prompt_en+',', num_return_sequences=1)[0]["generated_text"]   
-    else:
+    elif PM == 2:
         extend_prompt_en = extend_prompt_microsoft(prompt_en)
+    elif PM == 3:
+        extend_prompt_en = MagicPrompt(prompt_en)        
         
     if (prompt != prompt_en):
-        logger.info(f"extend_prompt__1_[{PM}]_")
+        logger.info(f"extend_prompt__1_PM=[{PM}]_")
         extend_prompt_out = getTextTrans(extend_prompt_en, source='en', target='zh')
     else:
-        logger.info(f"extend_prompt__2_[{PM}]_")
+        logger.info(f"extend_prompt__2_PM=[{PM}]_")
         extend_prompt_out = extend_prompt_en
 
     return extend_prompt_out
@@ -200,7 +269,24 @@ def prompt_extend_2(prompt):
     extend_prompt_out = prompt_extend(prompt, 2)
     return extend_prompt_out
 
-def prompt_draw(prompt):
+def prompt_extend_3(prompt):  
+    extend_prompt_out = prompt_extend(prompt, 3)
+    return extend_prompt_out    
+
+def prompt_draw_1(prompt, noise_level):
+    prompt_en = getTextTrans(prompt, source='zh', target='en')
+    if (prompt != prompt_en):
+        logger.info(f"draw_prompt______1__")
+        prompt_zh = prompt
+    else:
+        logger.info(f"draw_prompt______2__")
+        prompt_zh = getTextTrans(prompt, source='en', target='zh')
+
+    prompt_with_noise = add_random_noise(prompt_en, noise_level)
+    dreamlike_output = dreamlike_photoreal_2_0(prompt_with_noise)
+    return prompt_en, prompt_zh, dreamlike_output
+
+def prompt_draw_2(prompt):
     prompt_en = getTextTrans(prompt, source='zh', target='en')
     if (prompt != prompt_en):
         logger.info(f"draw_prompt______1__")
@@ -208,9 +294,8 @@ def prompt_draw(prompt):
     else:
         logger.info(f"draw_prompt______2__")
         prompt_zh = getTextTrans(prompt, source='en', target='zh')
-        
     return prompt_en, prompt_zh
-        
+
 with gr.Blocks(title='Text-to-Image') as demo:
     with gr.Group(elem_id="page_1", visible=True) as page_1:
         with gr.Box():            
@@ -224,25 +309,49 @@ with gr.Blocks(title='Text-to-Image') as demo:
                     with gr.Row(elem_id="input_col1_row1"):
                         prompt_input0 = gr.Textbox(lines=2, label="Original prompt", visible=True)
                     with gr.Row(elem_id="input_col1_row2"):
+                        prompt_work = gr.Textbox(lines=1, label="prompt_work", elem_id="prompt_work", visible=True)                        
+                    with gr.Row(elem_id="input_col1_row3"):
                         with gr.Column(elem_id="input_col1_row2_col0"):
                             draw_btn_0 = gr.Button(value = "Generate(original)", elem_id="draw-btn-0")
-                        with gr.Column(elem_id="input_col1_row2_col1"):
-                            extend_btn_1 = gr.Button(value = "Extend_1",elem_id="extend-btn-1")   
-                        with gr.Column(elem_id="input_col1_row2_col2"):
-                            extend_btn_2 = gr.Button(value = "Extend_2",elem_id="extend-btn-2")                              
+                        if extend_prompt_1:
+                            with gr.Column(elem_id="input_col1_row2_col1"):
+                                extend_btn_1 = gr.Button(value = "Extend_1",elem_id="extend-btn-1") 
+                        if extend_prompt_2:
+                            with gr.Column(elem_id="input_col1_row2_col2"):
+                                extend_btn_2 = gr.Button(value = "Extend_2",elem_id="extend-btn-2")
+                        if extend_prompt_3:                                
+                            with gr.Column(elem_id="input_col1_row2_col3"):
+                                extend_btn_3 = gr.Button(value = "Extend_3",elem_id="extend-btn-3") 
                 with gr.Column(id="input_col2"):
                     prompt_input1 = gr.Textbox(lines=2, label="Extend prompt", visible=True)
                     draw_btn_1 = gr.Button(value = "Generate(extend)", elem_id="draw-btn-1")
-                    prompt_work = gr.Textbox(lines=1, label="prompt_work", elem_id="prompt_work", visible=False)
-                    prompt_work_zh = gr.Textbox(lines=1, label="prompt_work_zh", elem_id="prompt_work_zh", visible=False)
+            with gr.Row(elem_id="prompt_row1"):
+                with gr.Column(id="input_col3"):
+                    with gr.Row(elem_id="input_col3_row2"):
+                        prompt_work_zh = gr.Textbox(lines=1, label="prompt_work_zh", elem_id="prompt_work_zh", visible=False)  
             with gr.Row(elem_id='tab_demo', visible=True).style(height=200):
                 tab_demo = gr.TabbedInterface(tab_actions, tab_titles) 
-            with gr.Row():
+            if do_dreamlike_photoreal:
+                with gr.Row():
+                    noise_level=gr.Slider(minimum=0.1, maximum=3, step=0.1, label="Dreamlike noise Level: [Higher noise level produces more diverse outputs, while lower noise level produces similar outputs.]")
+            with gr.Row():                
+                switch_tab_advanced_btn = gr.Button(value = "Switch_tab_advanced", elem_id="switch_tab_advanced_btn")
+                switch_tab_advanced_btn.click(fn=None, inputs=[], outputs=[], _js=switch_tab_advanced)   
+            with gr.Row():                
                 gr.HTML(f"<p>{thanks_info}</p>") 
 
-            extend_btn_1.click(fn=prompt_extend_1, inputs=[prompt_input0], outputs=[prompt_input1])
-            extend_btn_2.click(fn=prompt_extend_2, inputs=[prompt_input0], outputs=[prompt_input1])
-            draw_btn_0.click(fn=prompt_draw, inputs=[prompt_input0], outputs=[prompt_work, prompt_work_zh])
-            draw_btn_1.click(fn=prompt_draw, inputs=[prompt_input1], outputs=[prompt_work, prompt_work_zh])
+            if extend_prompt_1:
+                extend_btn_1.click(fn=prompt_extend_1, inputs=[prompt_input0], outputs=[prompt_input1])
+            if extend_prompt_2:
+                extend_btn_2.click(fn=prompt_extend_2, inputs=[prompt_input0], outputs=[prompt_input1])
+            if extend_prompt_3:                                
+                extend_btn_3.click(fn=prompt_extend_3, inputs=[prompt_input0], outputs=[prompt_input1])
+
+            if do_dreamlike_photoreal:
+                draw_btn_0.click(fn=prompt_draw_1, inputs=[prompt_input0, noise_level], outputs=[prompt_work, prompt_work_zh, dreamlike_image])
+                draw_btn_1.click(fn=prompt_draw_1, inputs=[prompt_input1, noise_level], outputs=[prompt_work, prompt_work_zh, dreamlike_image])
+            else:
+                draw_btn_0.click(fn=prompt_draw_2, inputs=[prompt_input0], outputs=[prompt_work, prompt_work_zh])
+                draw_btn_1.click(fn=prompt_draw_2, inputs=[prompt_input1], outputs=[prompt_work, prompt_work_zh])                
         
 demo.launch()