# file stuff import os from io import BytesIO #image generation stuff from PIL import Image # gradio / hf / image gen stuff import gradio as gr from dotenv import load_dotenv from google.cloud import aiplatform import vertexai from vertexai.preview.vision_models import ImageGenerationModel from vertexai import preview import uuid #for generating unique filenames # GCP credentials stuff import json import tempfile import pybase64 from google.oauth2 import service_account import google.auth load_dotenv() service_account_json = pybase64.b64decode(os.getenv("IMAGEN")) service_account_info = json.loads(service_account_json) credentials = service_account.Credentials.from_service_account_info(service_account_info) project="pdr-imagen" aiplatform.init(project=project, credentials=credentials) def generate_image(prompt,model_name): try: model = ImageGenerationModel.from_pretrained(model_name) response = model.generate_images( prompt=prompt, number_of_images=1, ) image_bytes = response[0]._image_bytes image_url = Image.open(BytesIO(image_bytes)) except Exception as e: print(e) raise gr.Error(f"An error occurred while generating the image for: {entry}") return image_url with gr.Blocks() as demo: gr.Markdown("#
Google Vertex Imagen Generator
") #instructions with gr.Accordion("Instructions & Tips",label="instructions",open=False): with gr.Row(): gr.Markdown("**Tips**: Use adjectives (size,color,mood), specify the visual style (realistic,cartoon,8-bit), explain the point of view (from above,first person,wide angle) ") #prompts with gr.Accordion("Prompt",label="Prompt",open=True): text = gr.Textbox(label="What do you want to create?", placeholder="Enter your text and then click on the \"Image Generate\" button") model = gr.Dropdown(choices=["imagegeneration@002", "imagegeneration@005"], label="Model", value="imagegeneration@005") with gr.Row(): btn = gr.Button("Generate Images") #output with gr.Accordion("Image Output",label="Image Output",open=True): output_image = gr.Image(label="Image") btn.click(fn=generate_image, inputs=[text, model ], outputs=output_image, api_name=False) text.submit(fn=generate_image, inputs=[text, model ], outputs=output_image, api_name="generate_image") # Generate an api endpoint in Gradio / HF demo.launch(share=False)