created app.py
Browse files
app.py
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import io
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from PIL import Image
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from IPython.display import Image as IPImage
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import requests
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import json
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import gradio as gr
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model_id_list = ['stablediffusionapi/dreamshaper-v7', 'runwayml/stable-diffusion-v1-5', 'stabilityai/stable-diffusion-2-1', 'digiplay/DreamShaper_7', 'hakurei/waifu-diffusion']
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#Text-to-image endpoint
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def get_completion(inputs, model_id, hf_api_key, parameters=None):
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ENDPOINT_URL='https://api-inference.huggingface.co/models/{}'.format(model_id)
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headers = {
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"Authorization": f"Bearer {hf_api_key}",
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"Content-Type": "application/json"
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}
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data = { "inputs": inputs }
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if parameters is not None:
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data.update({"parameters": parameters})
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response = requests.request("POST",
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ENDPOINT_URL,
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headers=headers,
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data=json.dumps(data))
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if 'error' in str(response.content):
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return None
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else:
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return IPImage(response.content)
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# A helper function to convert the bytes string into PIL image to send to API
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def bytes_to_pil_image(img_bytes):
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byte_stream = io.BytesIO(img_bytes)
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pil_image = Image.open(byte_stream)
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return pil_image
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def generate(hf_api_key, prompt):
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outputs = []
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for model_id in model_id_list:
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output = get_completion(prompt, model_id, hf_api_key)
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if output == None:
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outputs.append(output)
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else:
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pil_image = bytes_to_pil_image(output.data) # Use the corrected function here
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outputs.append(pil_image)
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return outputs
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with gr.Blocks() as demo:
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gr.Markdown("# Image Generation")
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with gr.Row():
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hf_api_key = gr.Textbox(label="API Key")
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with gr.Row():
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with gr.Column(scale=4):
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prompt = gr.Textbox(label="Your prompt") #Give prompt some real estate
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with gr.Column(scale=1, min_width=50):
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btn = gr.Button("Submit") #Submit button side by side!
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with gr.Row():
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with gr.Column():
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output1 = gr.Image(label= model_id_list[0])
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with gr.Column():
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output2 = gr.Image(label= model_id_list[1])
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with gr.Row():
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with gr.Column():
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output3 = gr.Image(label= model_id_list[2])
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with gr.Column():
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output4 = gr.Image(label= model_id_list[3])
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with gr.Column():
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output5 = gr.Image(label= model_id_list[4])
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btn.click(fn=generate, inputs=[hf_api_key, prompt], outputs=[output1,output2,output3,output4,output5])
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gr.close_all()
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demo.launch()
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