Add "send to txt2img" button to PNGInfo (#9)

- Add "send to txt2img" button to PNGInfo (bf9ad1e6fbede10b78960336c6829133a61025ba)
- Replace static model list with function for removing extension and id (33f7d493b13c46fe5889e7067b6ca1bbb67b42a9)
- Update app.py (516f2ad246531f25395b79d0e3d2cfbf8726db81)


Co-authored-by: Zenafey Baenro <zenafey@users.noreply.huggingface.co>

app.py

@@ -80,9 +80,86 @@ def image_to_base64(image_path):
 
     return img_str.decode('utf-8')  # Convert bytes to string
 
+def remove_id_and_ext(text):
+    text = re.sub(r'\[.*\]$', '', text)
+    extension = text[-12:].strip()
+    if extension == "safetensors":
+        text = text[:-13]
+    elif extension == "ckpt":
+        text = text[:-4]
+    return text
+
+def get_data(text):
+    results = {}
+    patterns = {
+        'prompt': r'(.*)',
+        'negative_prompt': r'Negative prompt: (.*)',
+        'steps': r'Steps: (\d+),',
+        'seed': r'Seed: (\d+),',
+        'sampler': r'Sampler:\s*([^\s,]+(?:\s+[^\s,]+)*)', 
+        'model': r'Model:\s*([^\s,]+)',
+        'cfg_scale': r'CFG scale:\s*([\d\.]+)',
+        'size': r'Size:\s*([0-9]+x[0-9]+)'
+        }
+    for key in ['prompt', 'negative_prompt', 'steps', 'seed', 'sampler', 'model', 'cfg_scale', 'size']:
+        match = re.search(patterns[key], text)
+        if match:
+            results[key] = match.group(1)
+        else:
+            results[key] = None
+    if results['size'] is not None:
+        w, h = results['size'].split("x")
+        results['w'] = w
+        results['h'] = h
+    else:
+        results['w'] = None
+        results['h'] = None
+    return results
+
+def send_to_txt2img(image):
+    
+    result = {tabs: gr.Tabs.update(selected="t2i")}
+
+    try:
+        text = image.info['parameters']
+        data = get_data(text)
+        result[prompt] = gr.update(value=data['prompt'])
+        result[negative_prompt] = gr.update(value=data['negative_prompt']) if data['negative_prompt'] is not None else gr.update()
+        result[steps] = gr.update(value=int(data['steps'])) if data['steps'] is not None else gr.update()
+        result[seed] = gr.update(value=int(data['seed'])) if data['seed'] is not None else gr.update()
+        result[cfg_scale] = gr.update(value=float(data['cfg_scale'])) if data['cfg_scale'] is not None else gr.update()
+        result[width] = gr.update(value=int(data['w'])) if data['w'] is not None else gr.update()
+        result[height] = gr.update(value=int(data['h'])) if data['h'] is not None else gr.update()
+        result[sampler] = gr.update(value=data['sampler']) if data['sampler'] is not None else gr.update()
+        if model in model_names:
+            result[model] = gr.update(value=model_names[model])
+        else:
+            result[model] = gr.update()
+        return result
+
+    except Exception as e:
+        print(e)
+        result[prompt] = gr.update()
+        result[negative_prompt] = gr.update()
+        result[steps] = gr.update()
+        result[seed] = gr.update()
+        result[cfg_scale] = gr.update()
+        result[width] = gr.update()
+        result[height] = gr.update()
+        result[sampler] = gr.update()
+        result[model] = gr.update()
+
+        return result
+
 
 
 prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY"))
+model_list = prodia_client.list_models()
+model_names = {}
+
+for model_name in model_list:
+    name_without_ext = remove_id_and_ext(model_name)
+    model_names[name_without_ext] = model_name
 
 def flip_text(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
     result = prodia_client.generate({
@@ -110,7 +187,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
 
-
+    
     with gr.Row():
         with gr.Column(scale=6):
             model = gr.Dropdown(interactive=True,value="absolutereality_v181.safetensors [3d9d4d2b]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
@@ -118,96 +195,99 @@ with gr.Blocks(css=css) as demo:
         with gr.Column(scale=1):
             gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI.<br>Powered by [Prodia](https://prodia.com).<br> For more features and faster gen times check out our [API Docs](https://docs.prodia.com/reference/getting-started-guide)")
 
-    with gr.Tab("txt2img"):
-        with gr.Row():
-            with gr.Column(scale=6, min_width=600):
-                prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
-                negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly")
-            with gr.Column():
-                text_button = gr.Button("Generate", variant='primary', elem_id="generate")
-                
-        with gr.Row():
-            with gr.Column(scale=3):
-                with gr.Tab("Generation"):
-                    with gr.Row():
-                        with gr.Column(scale=1):
-                            sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=[
-                                "Euler",
-                                "Euler a",
-                                "LMS",
-                                "Heun",
-                                "DPM2",
-                                "DPM2 a",
-                                "DPM++ 2S a",
-                                "DPM++ 2M",
-                                "DPM++ SDE",
-                                "DPM fast",
-                                "DPM adaptive",
-                                "LMS Karras",
-                                "DPM2 Karras",
-                                "DPM2 a Karras",
-                                "DPM++ 2S a Karras",
-                                "DPM++ 2M Karras",
-                                "DPM++ SDE Karras",
-                                "DDIM",
-                                "PLMS",
-                            ])
+    with gr.Tabs() as tabs:
+        with gr.Tab("txt2img", id='t2i'):
+            with gr.Row():
+                with gr.Column(scale=6, min_width=600):
+                    prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
+                    negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly")
+                with gr.Column():
+                    text_button = gr.Button("Generate", variant='primary', elem_id="generate")
+                    
+            with gr.Row():
+                with gr.Column(scale=3):
+                    with gr.Tab("Generation"):
+                        with gr.Row():
+                            with gr.Column(scale=1):
+                                sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=[
+                                    "Euler",
+                                    "Euler a",
+                                    "LMS",
+                                    "Heun",
+                                    "DPM2",
+                                    "DPM2 a",
+                                    "DPM++ 2S a",
+                                    "DPM++ 2M",
+                                    "DPM++ SDE",
+                                    "DPM fast",
+                                    "DPM adaptive",
+                                    "LMS Karras",
+                                    "DPM2 Karras",
+                                    "DPM2 a Karras",
+                                    "DPM++ 2S a Karras",
+                                    "DPM++ 2M Karras",
+                                    "DPM++ SDE Karras",
+                                    "DDIM",
+                                    "PLMS",
+                                ])
+                                
+                            with gr.Column(scale=1):
+                                steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1)
+    
+                        with gr.Row():
+                            with gr.Column(scale=1):
+                                width = gr.Slider(label="Width", maximum=1024, value=512, step=8)
+                                height = gr.Slider(label="Height", maximum=1024, value=512, step=8)
                             
-                        with gr.Column(scale=1):
-                            steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1)
-
-                    with gr.Row():
-                        with gr.Column(scale=1):
-                            width = gr.Slider(label="Width", maximum=1024, value=512, step=8)
-                            height = gr.Slider(label="Height", maximum=1024, value=512, step=8)
-                        
-                        with gr.Column(scale=1):
-                            batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
-                            batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
-
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
-                    seed = gr.Number(label="Seed", value=-1)
-
-                
-            with gr.Column(scale=2):
-                image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
-
-        text_button.click(flip_text, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
+                            with gr.Column(scale=1):
+                                batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
+                                batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
     
-    with gr.Tab("PNG Info"):
-        def plaintext_to_html(text, classname=None):
-            content = "<br>\n".join(html.escape(x) for x in text.split('\n'))
-
-            return f"<p class='{classname}'>{content}</p>" if classname else f"<p>{content}</p>"
-
-
-        def get_exif_data(image):
-            items = image.info
-
-            info = ''
-            for key, text in items.items():
-                info += f"""
-                <div>
-                <p><b>{plaintext_to_html(str(key))}</b></p>
-                <p>{plaintext_to_html(str(text))}</p>
-                </div>
-                """.strip()+"\n"
-
-            if len(info) == 0:
-                message = "Nothing found in the image."
-                info = f"<div><p>{message}<p></div>"
-
-            return info
-
-        with gr.Row():
-            with gr.Column():
-                image_input = gr.Image(type="pil")
-                
-            with gr.Column():
-                exif_output = gr.HTML(label="EXIF Data")
-
-        image_input.upload(get_exif_data, inputs=[image_input], outputs=exif_output)
-
+                        cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
+                        seed = gr.Number(label="Seed", value=-1)
+    
+                    
+                with gr.Column(scale=2):
+                    image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
+    
+            text_button.click(flip_text, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
+        
+        with gr.Tab("PNG Info"):
+            def plaintext_to_html(text, classname=None):
+                content = "<br>\n".join(html.escape(x) for x in text.split('\n'))
+    
+                return f"<p class='{classname}'>{content}</p>" if classname else f"<p>{content}</p>"
+    
+    
+            def get_exif_data(image):
+                items = image.info
+    
+                info = ''
+                for key, text in items.items():
+                    info += f"""
+                    <div>
+                    <p><b>{plaintext_to_html(str(key))}</b></p>
+                    <p>{plaintext_to_html(str(text))}</p>
+                    </div>
+                    """.strip()+"\n"
+    
+                if len(info) == 0:
+                    message = "Nothing found in the image."
+                    info = f"<div><p>{message}<p></div>"
+    
+                return info
+    
+            with gr.Row():
+                with gr.Column():
+                    image_input = gr.Image(type="pil")
+                    
+                with gr.Column():
+                    exif_output = gr.HTML(label="EXIF Data")
+                    send_to_txt2img_btn = gr.Button("Send to txt2img")
+    
+            image_input.upload(get_exif_data, inputs=[image_input], outputs=exif_output)
+            send_to_txt2img_btn.click(send_to_txt2img, inputs=[image_input], outputs=[tabs, prompt, negative_prompt, steps, seed,
+                                                                                          model, sampler, width, height, cfg_scale])
 
 demo.queue(concurrency_count=32)
 demo.launch()