JasonHong984/ImageProcessingApp

1import streamlit as st2import cv23import numpy as np4import random5import os6import zipfile7import shutil8from moviepy.editor import ImageSequenceClip9from PIL import Image10import io11 12# 定義生成白色矩形的函數13def generate_white_rectangles(14    image,  # 直接傳入圖像陣列15    min_width_ratio=0.2,16    min_height_ratio=0.2,17    max_width_ratio=0.5,18    max_height_ratio=0.5,19    num_rectangles_range=(2, 5),20    margin_ratio=0.0521):22    height, width, _ = image.shape23    min_width = int(width * min_width_ratio)24    min_height = int(height * min_height_ratio)25    max_width = int(width * max_width_ratio)26    max_height = int(height * max_height_ratio)27    margin = int(min(width, height) * margin_ratio)28    num_rectangles = random.randint(num_rectangles_range[0], num_rectangles_range[1])29 30    output = image.copy()31    positions = []32 33    random.seed(random.randint(0, 1000000))34 35    for _ in range(num_rectangles):36        for attempt in range(500):37            rect_width = random.randint(min_width, max_width)38            rect_height = random.randint(min_height, max_height)39            x = random.randint(0, width - rect_width)40            y = random.randint(0, height - rect_height)41            new_rect = (x, y, x + rect_width, y + rect_height)42 43            expanded_rect = (x - margin, y - margin, x + rect_width + margin, y + rect_height + margin)44 45            if expanded_rect[0] < 0 or expanded_rect[1] < 0 or expanded_rect[2] > width or expanded_rect[3] > height:46                continue47 48            overlap = False49            for (x1, y1, x2, y2) in positions:50                expanded_existing = (x1 - margin, y1 - margin, x2 + margin, y2 + margin)51                if not (expanded_rect[2] <= expanded_existing[0] or expanded_rect[0] >= expanded_existing[2] or52                        expanded_rect[3] <= expanded_existing[1] or expanded_rect[1] >= expanded_existing[3]):53                    overlap = True54                    break55 56            if not overlap:57                positions.append(new_rect)58                cv2.rectangle(output, (x, y), (x + rect_width, y + rect_height), (255, 255, 255), -1)59                break60 61    return output62 63# 定義生成影片的函數64def create_random_video(image_list, fps=2, frame_duration=0.5, total_duration=15):65    required_frames = int(total_duration / frame_duration)66 67    if len(image_list) < required_frames:68        image_list = random.choices(image_list, k=required_frames)69    else:70        image_list = random.sample(image_list, k=required_frames)71 72    random.shuffle(image_list)73 74    first_image = image_list[0]75    height, width, _ = first_image.shape76 77    processed_images = []78    for img in image_list:79        img_resized = cv2.resize(img, (width, height))80        img_rgb = cv2.cvtColor(img_resized, cv2.COLOR_BGR2RGB)81        processed_images.append(img_rgb)82 83    clip = ImageSequenceClip(processed_images, durations=[frame_duration] * len(processed_images))84    clip = clip.set_fps(fps)85 86    # 將影片寫入記憶體（BytesIO）87    video_io = io.BytesIO()88    clip.write_videofile("temp.mp4", codec="libx264", audio=False)89    with open("temp.mp4", "rb") as f:90        video_io.write(f.read())91    video_io.seek(0)92    os.remove("temp.mp4")  # 刪除臨時檔案93    return video_io94 95# Streamlit 應用主邏輯96def main():97    st.title("圖片處理與影片生成工具")98    st.subheader("上傳多張 JPG 或 PNG 圖片，我們將添加隨機白色矩形、保存處理後圖片並生成 15 秒影片（每張 0.5 秒）")99 100    uploaded_files = st.file_uploader("選擇圖片", type=["jpg", "jpeg", "png"], accept_multiple_files=True)101 102    if uploaded_files:103        # 創建臨時資料夾保存處理後圖片104        output_dir = "processed_images"105        if os.path.exists(output_dir):106            shutil.rmtree(output_dir)107        os.makedirs(output_dir)108 109        image_list = []110        processed_paths = []111 112        for uploaded_file in uploaded_files:113            # 讀取上傳的圖片114            image = Image.open(uploaded_file)115            image_np = np.array(image)116            if image_np.shape[2] == 4:  # 處理 PNG 的 RGBA117                image_np = cv2.cvtColor(image_np, cv2.COLOR_RGBA2BGR)118            else:119                image_np = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)120 121            # 生成處理後圖片122            processed_image = generate_white_rectangles(image_np)123 124            # 保存處理後圖片125            output_path = os.path.join(output_dir, f"masked_{uploaded_file.name}")126            cv2.imwrite(output_path, processed_image)127            processed_paths.append(output_path)128 129            image_list.append(processed_image)130 131        if image_list:132            st.success(f"已處理並保存 {len(image_list)} 張圖片！")133 134            # 顯示處理後圖片135            st.subheader("處理後的圖片")136            for img_path in processed_paths:137                st.image(img_path, caption=os.path.basename(img_path), use_column_width=True)138 139            # 生成影片140            with st.spinner("生成影片中..."):141                video_io = create_random_video(image_list)142 143            # 顯示影片144            st.video(video_io.read(), format="video/mp4")145 146            # 提供影片下載按鈕147            video_io.seek(0)148            st.download_button("下載影片", video_io, file_name="processed_video.mp4", mime="video/mp4")149 150            # 打包處理後圖片為 ZIP 並提供下載151            zip_io = io.BytesIO()152            with zipfile.ZipFile(zip_io, mode='w', compression=zipfile.ZIP_DEFLATED) as zipf:153                for root, _, files in os.walk(output_dir):154                    for file in files:155                        zipf.write(os.path.join(root, file), arcname=file)156            zip_io.seek(0)157            st.download_button("下載處理後圖片 ZIP", zip_io, file_name="processed_images.zip", mime="application/zip")158 159        # 清空臨時資料夾160        shutil.rmtree(output_dir)161 162# 運行 Streamlit 應用163if __name__ == "__main__":164    main()165