Update app.py

app.py

@@ -7,8 +7,7 @@ import os
 from io import BytesIO
 import html
 import re
-import PIL
-from PIL import Image  # Убедитесь, что PIL импортируется для работы с изображениями
+
 
 
 class Prodia:
@@ -17,63 +16,70 @@ class Prodia:
         self.headers = {
             "X-Prodia-Key": api_key
         }
-
+    
     def generate(self, params):
-        return self._post(f"{self.base}/sd/generate", params).json()
-
+        response = self._post(f"{self.base}/sd/generate", params)
+        return response.json()
+    
     def transform(self, params):
-        return self._post(f"{self.base}/sd/transform", params).json()
-
+        response = self._post(f"{self.base}/sd/transform", params)
+        return response.json()
+    
     def controlnet(self, params):
-        return self._post(f"{self.base}/sd/controlnet", params).json()
-
+        response = self._post(f"{self.base}/sd/controlnet", params)
+        return response.json()
+    
     def get_job(self, job_id):
-        return self._get(f"{self.base}/job/{job_id}").json()
+        response = self._get(f"{self.base}/job/{job_id}")
+        return response.json()
 
     def wait(self, job):
         job_result = job
+
         while job_result['status'] not in ['succeeded', 'failed']:
             time.sleep(0.25)
             job_result = self.get_job(job['job'])
+
         return job_result
 
     def list_models(self):
-        return self._get(f"{self.base}/sd/models").json()
+        response = self._get(f"{self.base}/sd/models")
+        return response.json()
 
     def list_samplers(self):
-        return self._get(f"{self.base}/sd/samplers").json()
+        response = self._get(f"{self.base}/sd/samplers")
+        return response.json()
 
-    # Изменение: добавлены повторные попытки при сбоях сети
     def _post(self, url, params):
-        headers = {**self.headers, "Content-Type": "application/json"}
-        for _ in range(3):
-            try:
-                response = requests.post(url, headers=headers, data=json.dumps(params))
-                response.raise_for_status()
-                return response
-            except requests.exceptions.RequestException as e:
-                print(f"Request failed: {e}, retrying...")
-                time.sleep(1)
-        raise Exception("Failed after 3 attempts")
-
-    # Изменение: добавлены повторные попытки при сбоях сети
+        headers = {
+            **self.headers,
+            "Content-Type": "application/json"
+        }
+        response = requests.post(url, headers=headers, data=json.dumps(params))
+
+        if response.status_code != 200:
+            raise Exception(f"Bad Prodia Response: {response.status_code}")
+
+        return response
+
     def _get(self, url):
-        for _ in range(3):
-            try:
-                response = requests.get(url, headers=self.headers)
-                response.raise_for_status()
-                return response
-            except requests.exceptions.RequestException as e:
-                print(f"Request failed: {e}, retrying...")
-                time.sleep(1)
-        raise Exception("Failed after 3 attempts")
-
-
-def image_to_base64(image, format="PNG"):
+        response = requests.get(url, headers=self.headers)
+
+        if response.status_code != 200:
+            raise Exception(f"Bad Prodia Response: {response.status_code}")
+
+        return response
+
+
+def image_to_base64(image):
+    # Convert the image to bytes
     buffered = BytesIO()
-    image.save(buffered, format=format)
-    img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
-    return img_str
+    image.save(buffered, format="PNG")  # You can change format to PNG if needed
+    
+    # Encode the bytes to base64
+    img_str = base64.b64encode(buffered.getvalue())
+
+    return img_str.decode('utf-8')  # Convert bytes to string
 
 
 def remove_id_and_ext(text):
@@ -86,44 +92,68 @@ def remove_id_and_ext(text):
     return text
 
 
-# Изменение: оптимизация функции get_data
 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,]+)*)',
+        '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]+)'
-    }
-    results = {key: re.search(pattern, text).group(1) if re.search(pattern, text) else None for key, pattern in patterns.items()}
-    if results['size']:
-        results['w'], results['h'] = map(int, results['size'].split("x"))
+        }
+    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'], results['h'] = None, None
+        results['w'] = None
+        results['h'] = None
     return results
 
 
-# Изменение: оптимизация функции send_to_txt2img
 def send_to_txt2img(image):
+
     result = {tabs: gr.update(selected="t2i")}
+
     try:
         text = image.info['parameters']
         data = get_data(text)
-        fields = ['prompt', 'negative_prompt', 'steps', 'seed', 'cfg_scale', 'w', 'h', 'sampler', 'model']
-        for field in fields:
-            result[field] = gr.update(value=data[field]) if data[field] is not None else gr.update()
+        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)
+
         return result
 
 
 prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY"))
 model_list = prodia_client.list_models()
-model_names = {remove_id_and_ext(model_name): model_name for model_name in model_list}
+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 txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
@@ -138,7 +168,9 @@ def txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, he
         "height": height,
         "seed": seed
     })
+
     job = prodia_client.wait(result)
+
     return job["imageUrl"]
 
 
@@ -156,7 +188,9 @@ def img2img(input_image, denoising, prompt, negative_prompt, model, steps, sampl
         "height": height,
         "seed": seed
     })
+
     job = prodia_client.wait(result)
+
     return job["imageUrl"]
 
 
@@ -169,7 +203,7 @@ css = """
 with gr.Blocks(css=css) as demo:
     with gr.Row():
         with gr.Column(scale=6):
-            model = gr.Dropdown(interactive=True, value="childrensStories_v1ToonAnime.safetensors [2ec7b88b]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
+            model = gr.Dropdown(interactive=True,value="childrensStories_v1ToonAnime.safetensors [2ec7b88b]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
   
         with gr.Column(scale=1):
             gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI переделано masteroko.<br>Powered by [Prodia](https://prodia.com).<br>For more features and faster generation times check out our [API Docs](https://docs.prodia.com/reference/getting-started-guide).")
@@ -208,46 +242,86 @@ with gr.Blocks(css=css) as demo:
                 with gr.Column(scale=2):
                     image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
     
-            # Изменение: добавлен limit на одновременные запросы
-            text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output, concurrency_limit=1024)
+            text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height,
+                                               seed], outputs=image_output, concurrency_limit=1024)
         
         with gr.Tab("img2img", id='i2i'):
             with gr.Row():
                 with gr.Column(scale=6, min_width=600):
-                    image = gr.Image(show_label=False)
-                    prompt = gr.Textbox(placeholder="Prompt", show_label=False, lines=3)
-                    negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3)
+                    i2i_prompt = gr.Textbox("тута переделай фотку ", placeholder="Prompt", show_label=False, lines=3)
+                    i2i_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("Трансформировать", variant='primary', elem_id="generate")
+                    i2i_text_button = gr.Button("Сгенерировать", variant='primary', elem_id="generate")
                     
             with gr.Row():
                 with gr.Column(scale=3):
                     with gr.Tab("Генерация"):
+                        i2i_image_input = gr.Image(type="pil")
+
                         with gr.Row():
                             with gr.Column(scale=1):
-                                sampler = gr.Dropdown(value="DPM++ 2M SDE Exponential", show_label=True, label="Sampling Method", choices=prodia_client.list_samplers())
+                                i2i_sampler = gr.Dropdown(value="DPM++ 3M SDE Exponential", show_label=True, label="Sampling Method", choices=prodia_client.list_samplers())
                                 
                             with gr.Column(scale=1):
-                                steps = gr.Slider(label="количество обработок", minimum=1, maximum=100, value=20, step=1)
-    
+                                i2i_steps = gr.Slider(label="количество обработок", minimum=1, maximum=100, value=20, step=1)
+
                         with gr.Row():
                             with gr.Column(scale=1):
-                                width = gr.Slider(label="Ширина", maximum=1024, value=512, step=8)
-                                height = gr.Slider(label="Высота", maximum=1024, value=512, step=8)
+                                i2i_width = gr.Slider(label="Ширина", maximum=1024, value=512, step=8)
+                                i2i_height = gr.Slider(label="Высота", 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)
+                                i2i_batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
+                                i2i_batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
     
-                        cfg_scale = gr.Slider(label="CFG Scale(степень фантазии ии)", minimum=1, maximum=20, value=7, step=1)
-                        seed = gr.Number(label="Семя рандома", value=-1)
-                        denoising = gr.Slider(label="Denoising", value=0.5)
+                        i2i_cfg_scale = gr.Slider(label="CFG Scale(степень фантазии ии)", minimum=1, maximum=20, value=7, step=1)
+                        i2i_denoising = gr.Slider(label="сила изменения фото", minimum=0, maximum=5, value=0.7, step=0.05)
+                        i2i_seed = gr.Number(label="Семя рандома ", value=-1)
 
                 with gr.Column(scale=2):
-                    image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
+                    i2i_image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
     
-            # Изменение: добавлен limit на одновременные запросы
-            text_button.click(img2img, inputs=[image, denoising, prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output, concurrency_limit=1024)
-            
-# Запуск Gradio интерфейса
-demo.launch()
+            i2i_text_button.click(img2img, inputs=[i2i_image_input, i2i_denoising, i2i_prompt, i2i_negative_prompt,
+                                                   model, i2i_steps, i2i_sampler, i2i_cfg_scale, i2i_width, i2i_height,
+                                                   i2i_seed], outputs=i2i_image_output, concurrency_limit=1024)
+        
+        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("копировать в данные в 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],
+                                      concurrency_limit=1024)
+
+demo.queue(max_size=80, api_open=False).launch(max_threads=8192, show_api=False)