change back to streamlit
Browse files- README.md +2 -2
- app.py +29 -32
- baseline_utils.py +1 -1
- requirements.txt +1 -1
README.md
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@@ -3,8 +3,8 @@ title: Diary-AI
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emoji: π
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colorFrom: red
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colorTo: blue
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sdk:
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sdk_version: "
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app_file: app.py
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pinned: false
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---
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emoji: π
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colorFrom: red
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colorTo: blue
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sdk: streamlit
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sdk_version: "1.38.0"
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app_file: app.py
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pinned: false
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---
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app.py
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@@ -1,4 +1,4 @@
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import
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import openai
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import json
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from PIL import Image
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@@ -7,19 +7,30 @@ from baseline_utils import detect_text_in_image, summarize_diary_text, analyze_w
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import glob
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import os
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# Load secrets
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openai_api_key =
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google_service_account_info = json.loads(
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gemini_api_key =
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# Function to get Google credentials
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def get_google_credentials():
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return service_account.Credentials.from_service_account_info(google_service_account_info)
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diary_image_path = "temp_upload_images/temp_diary_image.png"
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writer_image_path = "temp_upload_images/temp_writer_image.png"
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os.makedirs("temp_upload_images", exist_ok=True)
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@@ -30,39 +41,25 @@ def process_images(diary_image, writer_image):
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google_credentials = get_google_credentials()
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detected_text = detect_text_in_image(diary_image_path, google_credentials)
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summarized_text = summarize_diary_text(detected_text, openai_api_key)
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# Analyze the writer's image using Gemini API
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writer_summary = analyze_writer_image(writer_image_path, gemini_api_key)
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# Generate the comic book based on the summaries
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generate_comic_book(summarized_text, writer_summary, num_pages=4)
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# Assuming generated images are saved as 'comic_book/page_1.png', 'comic_book/page_2.png', etc.
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image_files = sorted(glob.glob("comic_book/page_*.png")) # Find all the generated comic book pages
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# Define the Gradio interface
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def gradio_interface(diary_image, writer_image):
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# Process the images and generate comic book pages
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generated_images = process_images(diary_image, writer_image)
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# Load the images and return them
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images = [Image.open(img) for img in generated_images]
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return images
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# Set up the Gradio interface
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interface = gr.Interface(
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fn=gradio_interface,
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inputs=[
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gr.Image(label="Upload your handwritten diary image", type="pil"),
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gr.Image(label="Upload a photo of the writer", type="pil"),
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],
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outputs=gr.Gallery(label="Generated Comic Book Pages"),
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title="Handwritten Diary to Comic Book"
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)
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import streamlit as st
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import openai
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import json
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from PIL import Image
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import glob
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import os
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# Load secrets
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openai_api_key = st.secrets["openai_api_key"]
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google_service_account_info = json.loads(st.secrets["google_service_account"])
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gemini_api_key = st.secrets["gemini_api_key"]
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# Initialize OpenAI
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openai.api_key = openai_api_key
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# Function to get Google credentials
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def get_google_credentials():
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return service_account.Credentials.from_service_account_info(google_service_account_info)
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st.title('Handwritten Diary to Comic Book')
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uploaded_diary = st.file_uploader("Upload your handwritten diary image", type=["png", "jpg", "jpeg"])
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uploaded_writer_image = st.file_uploader("Upload a photo of the writer", type=["png", "jpg", "jpeg"])
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if uploaded_diary and uploaded_writer_image:
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st.write("Analyzing your diary and writer...")
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# Read the uploaded images using file-like objects
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diary_image = Image.open(uploaded_diary)
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writer_image = Image.open(uploaded_writer_image)
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# Save the file-like objects as image files (optional if needed)
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diary_image_path = "temp_upload_images/temp_diary_image.png"
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writer_image_path = "temp_upload_images/temp_writer_image.png"
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os.makedirs("temp_upload_images", exist_ok=True)
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google_credentials = get_google_credentials()
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detected_text = detect_text_in_image(diary_image_path, google_credentials)
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summarized_text = summarize_diary_text(detected_text, openai_api_key)
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st.write(f"Summarized Diary Text: {summarized_text}")
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# Analyze the writer's image using Gemini API
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writer_summary = analyze_writer_image(writer_image_path, gemini_api_key)
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st.write(f"Writer Description: {writer_summary}")
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# Generate the comic book based on the summaries
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st.write("Generating comic book images...")
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generate_comic_book(summarized_text, writer_summary, num_pages=4)
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st.write("Comic book generated successfully!")
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# Assuming generated images are saved as 'comic_book/page_1.png', 'comic_book/page_2.png', etc.
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image_files = sorted(glob.glob("comic_book/page_*.png")) # Find all the generated comic book pages
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# Display images in 2 columns
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cols = st.columns(2) # Create two columns for the images
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for i, image_file in enumerate(image_files):
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with cols[i % 2]: # Alternate between the two columns
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# Display each comic book page in the respective column
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st.image(image_file, caption=image_file.split('/')[-1], use_column_width=True)
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baseline_utils.py
CHANGED
@@ -79,7 +79,7 @@ def generate_comic_book(diary_text, writer_description, num_pages=4):
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"stabilityai/sdxl-turbo",
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torch_dtype=torch.float16,
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variant="fp16",
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)
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# Check for available device: CUDA, MPS, or CPU
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"stabilityai/sdxl-turbo",
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torch_dtype=torch.float16,
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variant="fp16",
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cache_dir="./SDXL-Turbo"
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)
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# Check for available device: CUDA, MPS, or CPU
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requirements.txt
CHANGED
@@ -5,5 +5,5 @@ google-generativeai
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diffusers
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torch
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gradio
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transformers
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accelerate
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diffusers
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torch
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gradio
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transformers
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accelerate
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