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import os |
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import glob |
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import time |
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import streamlit as st |
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import fitz |
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import requests |
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from PIL import Image |
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from transformers import AutoTokenizer, AutoModel |
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from diffusers import StableDiffusionPipeline |
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import cv2 |
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import numpy as np |
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import logging |
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import asyncio |
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import aiofiles |
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from io import BytesIO |
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") |
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logger = logging.getLogger(__name__) |
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log_records = [] |
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class LogCaptureHandler(logging.Handler): |
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def emit(self, record): |
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log_records.append(record) |
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logger.addHandler(LogCaptureHandler()) |
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st.set_page_config( |
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page_title="AI Vision Titans 🚀", |
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page_icon="🤖", |
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layout="wide", |
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initial_sidebar_state="expanded", |
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menu_items={'About': "AI Vision Titans: PDF Snapshots, OCR, Image Gen, Line Drawings on CPU! 🌌"} |
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) |
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if 'captured_files' not in st.session_state: |
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st.session_state['captured_files'] = [] |
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if 'processing' not in st.session_state: |
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st.session_state['processing'] = {} |
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def generate_filename(sequence, ext="png"): |
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timestamp = time.strftime("%d%m%Y%H%M%S") |
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return f"{sequence}{timestamp}.{ext}" |
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def get_gallery_files(file_types): |
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return sorted([f for ext in file_types for f in glob.glob(f"*.{ext}")]) |
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def update_gallery(): |
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media_files = get_gallery_files(["png", "txt"]) |
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if media_files: |
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cols = st.sidebar.columns(2) |
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for idx, file in enumerate(media_files[:gallery_size * 2]): |
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with cols[idx % 2]: |
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if file.endswith(".png"): |
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st.image(Image.open(file), caption=file, use_container_width=True) |
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elif file.endswith(".txt"): |
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with open(file, "r") as f: |
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content = f.read() |
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st.text(content[:50] + "..." if len(content) > 50 else content, help=file) |
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def download_pdf(url, output_path): |
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try: |
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response = requests.get(url, stream=True, timeout=10) |
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if response.status_code == 200: |
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with open(output_path, "wb") as f: |
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for chunk in response.iter_content(chunk_size=8192): |
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f.write(chunk) |
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return True |
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except requests.RequestException as e: |
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logger.error(f"Failed to download {url}: {e}") |
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return False |
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def load_ocr_got(): |
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model_id = "ucaslcl/GOT-OCR2_0" |
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True) |
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model = AutoModel.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.float32).to("cpu").eval() |
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return tokenizer, model |
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def load_image_gen(): |
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model_id = "OFA-Sys/small-stable-diffusion-v0" |
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pipeline = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32).to("cpu") |
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return pipeline |
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def load_line_drawer(): |
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def edge_detection(image, style="fine"): |
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img_np = np.array(image.convert("RGB")) |
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gray = cv2.cvtColor(img_np, cv2.COLOR_RGB2GRAY) |
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if style == "fine": |
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edges = cv2.Canny(gray, 50, 150) |
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else: |
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edges = cv2.Canny(gray, 100, 200) |
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return Image.fromarray(edges) |
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return edge_detection |
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async def process_pdf_snapshot(pdf_path, mode="thumbnail"): |
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start_time = time.time() |
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status = st.empty() |
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status.text(f"Processing PDF Snapshot ({mode})... (0s)") |
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doc = fitz.open(pdf_path) |
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output_files = [] |
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if mode == "thumbnail": |
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page = doc[0] |
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pix = page.get_pixmap(matrix=fitz.Matrix(0.5, 0.5)) |
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output_file = generate_filename("thumbnail", "png") |
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pix.save(output_file) |
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output_files.append(output_file) |
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elif mode == "twopage": |
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for i in range(min(2, len(doc))): |
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page = doc[i] |
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pix = page.get_pixmap(matrix=fitz.Matrix(1.0, 1.0)) |
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output_file = generate_filename(f"twopage_{i}", "png") |
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pix.save(output_file) |
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output_files.append(output_file) |
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doc.close() |
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elapsed = int(time.time() - start_time) |
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status.text(f"PDF Snapshot ({mode}) completed in {elapsed}s!") |
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for file in output_files: |
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if file not in st.session_state['captured_files']: |
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st.session_state['captured_files'].append(file) |
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update_gallery() |
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return output_files |
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async def process_ocr(image, output_file): |
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start_time = time.time() |
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status = st.empty() |
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status.text("Processing GOT-OCR2_0... (0s)") |
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tokenizer, model = load_ocr_got() |
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result = model.chat(tokenizer, image, ocr_type='ocr') |
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elapsed = int(time.time() - start_time) |
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status.text(f"GOT-OCR2_0 completed in {elapsed}s!") |
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async with aiofiles.open(output_file, "w") as f: |
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await f.write(result) |
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if output_file not in st.session_state['captured_files']: |
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st.session_state['captured_files'].append(output_file) |
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update_gallery() |
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return result |
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async def process_image_gen(prompt, output_file): |
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start_time = time.time() |
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status = st.empty() |
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status.text("Processing Image Gen... (0s)") |
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pipeline = load_image_gen() |
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gen_image = pipeline(prompt, num_inference_steps=20).images[0] |
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elapsed = int(time.time() - start_time) |
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status.text(f"Image Gen completed in {elapsed}s!") |
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gen_image.save(output_file) |
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if output_file not in st.session_state['captured_files']: |
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st.session_state['captured_files'].append(output_file) |
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update_gallery() |
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return gen_image |
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async def process_line_drawing(image, style, output_file): |
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start_time = time.time() |
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status = st.empty() |
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status.text(f"Processing Line Drawing ({style})... (0s)") |
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edge_fn = load_line_drawer() |
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line_drawing = edge_fn(image, style=style) |
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elapsed = int(time.time() - start_time) |
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status.text(f"Line Drawing ({style}) completed in {elapsed}s!") |
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line_drawing.save(output_file) |
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if output_file not in st.session_state['captured_files']: |
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st.session_state['captured_files'].append(output_file) |
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update_gallery() |
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return line_drawing |
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st.title("AI Vision Titans 🚀") |
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st.sidebar.header("Captured Files 📜") |
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gallery_size = st.sidebar.slider("Gallery Size", 1, 10, 4) |
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update_gallery() |
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st.sidebar.subheader("Action Logs 📜") |
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log_container = st.sidebar.empty() |
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with log_container: |
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for record in log_records: |
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st.write(f"{record.asctime} - {record.levelname} - {record.message}") |
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tab1, tab2, tab3, tab4, tab5 = st.tabs(["Camera Snap 📷", "Download PDFs 📥", "Test OCR 🔍", "Test Image Gen 🎨", "Test Line Drawings ✏️"]) |
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with tab1: |
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st.header("Camera Snap 📷") |
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st.subheader("Single Capture") |
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cols = st.columns(2) |
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with cols[0]: |
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cam0_img = st.camera_input("Take a picture - Cam 0", key="cam0") |
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if cam0_img: |
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filename = generate_filename(0) |
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if filename not in st.session_state['captured_files']: |
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with open(filename, "wb") as f: |
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f.write(cam0_img.getvalue()) |
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st.image(Image.open(filename), caption=filename, use_container_width=True) |
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logger.info(f"Saved snapshot from Camera 0: {filename}") |
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st.session_state['captured_files'].append(filename) |
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update_gallery() |
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with cols[1]: |
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cam1_img = st.camera_input("Take a picture - Cam 1", key="cam1") |
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if cam1_img: |
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filename = generate_filename(1) |
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if filename not in st.session_state['captured_files']: |
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with open(filename, "wb") as f: |
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f.write(cam1_img.getvalue()) |
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st.image(Image.open(filename), caption=filename, use_container_width=True) |
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logger.info(f"Saved snapshot from Camera 1: {filename}") |
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st.session_state['captured_files'].append(filename) |
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update_gallery() |
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st.subheader("Burst Capture") |
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slice_count = st.number_input("Number of Frames", min_value=1, max_value=20, value=10, key="burst_count") |
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if st.button("Start Burst Capture 📸"): |
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st.session_state['burst_frames'] = [] |
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placeholder = st.empty() |
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for i in range(slice_count): |
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with placeholder.container(): |
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st.write(f"Capturing frame {i+1}/{slice_count}...") |
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img = st.camera_input(f"Frame {i}", key=f"burst_{i}_{time.time()}") |
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if img: |
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filename = generate_filename(f"burst_{i}") |
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if filename not in st.session_state['captured_files']: |
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with open(filename, "wb") as f: |
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f.write(img.getvalue()) |
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st.session_state['burst_frames'].append(filename) |
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logger.info(f"Saved burst frame {i}: {filename}") |
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st.image(Image.open(filename), caption=filename, use_container_width=True) |
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time.sleep(0.5) |
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st.session_state['captured_files'].extend([f for f in st.session_state['burst_frames'] if f not in st.session_state['captured_files']]) |
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update_gallery() |
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placeholder.success(f"Captured {len(st.session_state['burst_frames'])} frames!") |
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with tab2: |
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st.header("Download PDFs 📥") |
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url_input = st.text_area("Enter PDF URLs (one per line)", height=100) |
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mode = st.selectbox("Snapshot Mode", ["Thumbnail", "Two-Page View"], key="download_mode") |
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if st.button("Download & Snapshot 📸"): |
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urls = url_input.strip().split("\n") |
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for url in urls: |
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if url: |
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pdf_path = generate_filename("downloaded", "pdf") |
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if download_pdf(url, pdf_path): |
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logger.info(f"Downloaded PDF from {url} to {pdf_path}") |
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snapshots = asyncio.run(process_pdf_snapshot(pdf_path, mode.lower().replace(" ", ""))) |
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for snapshot in snapshots: |
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st.image(Image.open(snapshot), caption=snapshot, use_container_width=True) |
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else: |
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st.error(f"Failed to download {url}") |
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with tab3: |
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st.header("Test OCR 🔍") |
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captured_files = get_gallery_files(["png"]) |
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if captured_files: |
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selected_file = st.selectbox("Select Image", captured_files, key="ocr_select") |
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image = Image.open(selected_file) |
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st.image(image, caption="Input Image", use_container_width=True) |
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if st.button("Run OCR 🚀", key="ocr_run"): |
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output_file = generate_filename("ocr_output", "txt") |
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st.session_state['processing']['ocr'] = True |
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result = asyncio.run(process_ocr(image, output_file)) |
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st.text_area("OCR Result", result, height=200, key="ocr_result") |
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st.success(f"OCR output saved to {output_file}") |
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st.session_state['processing']['ocr'] = False |
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else: |
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st.warning("No images captured yet. Use Camera Snap or Download PDFs first!") |
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with tab4: |
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st.header("Test Image Gen 🎨") |
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captured_files = get_gallery_files(["png"]) |
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if captured_files: |
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selected_file = st.selectbox("Select Image", captured_files, key="gen_select") |
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image = Image.open(selected_file) |
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st.image(image, caption="Reference Image", use_container_width=True) |
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prompt = st.text_area("Prompt", "Generate a similar superhero image", key="gen_prompt") |
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if st.button("Run Image Gen 🚀", key="gen_run"): |
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output_file = generate_filename("gen_output", "png") |
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st.session_state['processing']['gen'] = True |
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result = asyncio.run(process_image_gen(prompt, output_file)) |
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st.image(result, caption="Generated Image", use_container_width=True) |
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st.success(f"Image saved to {output_file}") |
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st.session_state['processing']['gen'] = False |
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else: |
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st.warning("No images captured yet. Use Camera Snap or Download PDFs first!") |
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with tab5: |
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st.header("Test Line Drawings ✏️") |
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captured_files = get_gallery_files(["png"]) |
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if captured_files: |
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selected_file = st.selectbox("Select Image", captured_files, key="line_select") |
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image = Image.open(selected_file) |
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st.image(image, caption="Input Image", use_container_width=True) |
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style = st.selectbox("Line Style", ["Fine", "Bold"], key="line_style") |
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if st.button("Run Line Drawing 🚀", key="line_run"): |
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output_file = generate_filename(f"line_{style.lower()}", "png") |
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st.session_state['processing']['line'] = True |
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result = asyncio.run(process_line_drawing(image, style.lower(), output_file)) |
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st.image(result, caption=f"{style} Line Drawing", use_container_width=True) |
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st.success(f"Line drawing saved to {output_file}") |
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st.session_state['processing']['line'] = False |
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else: |
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st.warning("No images captured yet. Use Camera Snap or Download PDFs first!") |
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update_gallery() |