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Update app.py
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app.py
CHANGED
@@ -1,22 +1,17 @@
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## app.py:
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import torch
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import gradio as gr
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from diffusers import StableDiffusionPipeline
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import requests
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from io import BytesIO
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import os
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from PIL import Image
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def translate_text(text, target_language='en'):
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API_URL = "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-ar-en"
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headers = {"Authorization": f"Bearer {os.getenv('API_TOKEN')}"}
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response = requests.post(API_URL, headers=headers, json=text)
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if response.status_code == 200:
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return response.json()[0]['translation_text']
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else:
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print("Failed to translate text:", response.text)
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return text # Return the original text if translation fails
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@@ -30,14 +25,13 @@ def query(payload, API_URL, headers):
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def generate_image(prompt, model_choice, translate=False):
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if translate:
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prompt = translate_text(prompt, target_language='en') # Assuming you want to translate to English
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model_urls = {
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"Stable Diffusion v1.5": "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5",
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"dalle-3-xl-v2": "https://api-inference.huggingface.co/models/ehristoforu/dalle-3-xl-v2",
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"midjourney-v6": "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v6",
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"openjourney-v4": "https://api-inference.huggingface.co/models/prompthero/openjourney-v4",
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"LCM_Dreamshaper_v7": "https://api-inference.huggingface.co/models/SimianLuo/LCM_Dreamshaper_v7",
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}
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API_URL = model_urls[model_choice]
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@@ -49,10 +43,6 @@ def generate_image(prompt, model_choice, translate=False):
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image = Image.open(BytesIO(data))
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# Resize the image
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image = image.resize((400, 400))
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# Convert the image object back to bytes for Gradio output
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buf = BytesIO()
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image.save(buf, format='PNG')
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buf.seek(0)
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return image
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except Exception as e:
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@@ -75,11 +65,11 @@ description = "اكتب وصف للصورة التي تود من النظام ا
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iface = gr.Interface(
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fn=generate_image,
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inputs=[
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gr.
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gr.
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gr.
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],
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outputs=gr.
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title=title,
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description=description,
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theme="default",
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import torch
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import gradio as gr
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import requests
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from io import BytesIO
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from PIL import Image
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import os
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def translate_text(text, target_language='en'):
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API_URL = "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-ar-en"
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headers = {"Authorization": f"Bearer {os.getenv('API_TOKEN')}"}
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response = requests.post(API_URL, headers=headers, json={"inputs": text})
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if response.status_code == 200:
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return response.json()[0]['translation_text']
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else:
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print("Failed to translate text:", response.text)
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return text # Return the original text if translation fails
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def generate_image(prompt, model_choice, translate=False):
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if translate:
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prompt = translate_text(prompt, target_language='en') # Assuming you want to translate to English
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model_urls = {
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"Stable Diffusion v1.5": "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5",
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"dalle-3-xl-v2": "https://api-inference.huggingface.co/models/ehristoforu/dalle-3-xl-v2",
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"midjourney-v6": "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v6",
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"openjourney-v4": "https://api-inference.huggingface.co/models/prompthero/openjourney-v4",
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"LCM_Dreamshaper_v7": "https://api-inference.huggingface.co/models/SimianLuo/LCM_Dreamshaper_v7",
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}
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API_URL = model_urls[model_choice]
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image = Image.open(BytesIO(data))
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# Resize the image
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image = image.resize((400, 400))
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return image
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except Exception as e:
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iface = gr.Interface(
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fn=generate_image,
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inputs=[
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gr.Textbox(lines=2, placeholder="Enter the description of the image here..."),
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gr.Dropdown(choices=["Stable Diffusion v1.5","dalle-3-xl-v2","midjourney-v6","openjourney-v4","LCM_Dreamshaper_v7"], label="Choose Model", value='Stable Diffusion v1.5'),
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gr.Checkbox(label="Translate The Text Before Generating Image", value=False)
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],
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outputs=gr.Image(),
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title=title,
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description=description,
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theme="default",
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