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# 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 | |
# GCP credentials stuff | |
import json | |
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("# <center>Google Vertex Imagen Generator</center>") | |
#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) |