feat: single mode

Signed-off-by: longshiine <[email protected]>

app.py

@@ -1,7 +1,241 @@
+import requests
 import gradio as gr
+import zipfile
+from PIL import Image
+from io import BytesIO
+from rembg import remove
 
-def greet(name):
-    return "Hello " + name + "!!"
+def download_image(image_url: str) -> Image.Image:
+    # 이미지 다운로드
+    response = requests.get(image_url)
+    
+    if response.status_code == 200:
+        original_image = Image.open(BytesIO(response.content))
+        return original_image
+    else:
+        raise Exception(f"Failed to download image. Status code: {response.status_code}")
+
+def remove_background(image: Image.Image) -> Image.Image:
+    # 이미지 누끼따기
+    try:
+        removebg_image = remove(
+            image,
+            post_process_mask=True,
+            alpha_matting=True, 
+            alpha_matting_foreground_threshold=270,
+            alpha_matting_background_threshold=30, 
+            alpha_matting_erode_size=15)
+        return removebg_image
+    
+    except Exception as e:
+        print(f"Failed to remove background: {e}")
+        return None
+    
+def crop_image(image: Image.Image) -> Image.Image:
+    # 이미지 크롭
+    try:
+        # 알파 채널을 사용하여 이미지의 경계 영역 찾기
+        bbox = image.getbbox()
+        if bbox:
+            # 경계 상자로 이미지 크롭
+            cropped_image = image.crop(bbox)
+            return cropped_image
+        else:
+            print("No bounding box found.")
+            return image
+    
+    except Exception as e:
+        print(f"Failed to crop image: {e}")
+        return None
+      
+def resize_image(image: Image.Image, max_size: int) -> Image.Image:
+    # 이미지 크기 조정
+    try:
+        # 이미지의 현재 너비와 높이 가져오기
+        width, height = image.size
+        
+        # 너비와 높이 중 더 큰 쪽의 비율에 맞춰 크기를 조정
+        if width > height:
+            new_width = max_size
+            new_height = int((max_size / width) * height)
+        else:
+            new_height = max_size
+            new_width = int((max_size / height) * width)
+        
+        resized_image = image.resize((new_width, new_height))
+        return resized_image
+    
+    except Exception as e:
+        print(f"Failed to resize image: {e}")
+        return None
+    
+def paste_to_background_type_a(background: Image.Image, product: Image.Image) -> Image.Image:
+    # 배경에 제품 이미지 합성
+    try:
+        # 배경 이미지 크기 가져오기
+        bg_width, bg_height = background.size
+        
+        # 제품 이미지 크기 가져오기
+        product_width, product_height = product.size
+        
+        # 제품 이미지를 배경 이미지 중앙에 위치시키기
+        offset = ((bg_width - product_width) // 2, (bg_height - product_height) // 2)
+        
+        # 알파 채널을 고려하여 합성
+        background.paste(product, offset, mask=product)
+        return background
+    
+    except Exception as e:
+        print(f"Failed to paste product image to background: {e}")
+        return None
+    
+def paste_to_background_type_b(background: Image.Image, product: Image.Image, margin: int = 10) -> Image.Image:
+    try:
+        # 배경 이미지 크기 가져오기
+        bg_width, bg_height = background.size
+        
+        # 제품 이미지 크기 가져오기
+        product_width, product_height = product.size
+        
+        # 두 제품 이미지를 위한 전체 너비 계산 (제품 이미지 두 개 + 마진)
+        total_width = (product_width * 2) + margin
+        
+        if total_width > bg_width:
+            raise ValueError("Background is too narrow to fit two product images with the specified margin.")
+        
+        # 첫 번째 제품 이미지의 왼쪽 상단 좌표 계산
+        left_offset = (bg_width - total_width) // 2
+        top_offset = (bg_height - product_height) // 2
+        
+        # 두 번째 제품 이미지의 왼쪽 상단 좌표 계산
+        right_offset = left_offset + product_width + margin
+        
+        # 첫 번째 제품 이미지 배경에 합성
+        background.paste(product, (left_offset, top_offset), mask=product)
+        
+        # 두 번째 제품 이미지 배경에 합성
+        background.paste(product, (right_offset, top_offset), mask=product)
+        return background
+    
+    except Exception as e:
+        print(f"Failed to paste product images to background: {e}")
+        return None
+
+def paste_to_background_type_c(background: Image.Image, product: Image.Image, margin: int = 10, top_margin: int = 15) -> Image.Image:
+    try:
+        # 배경 이미지 크기 가져오기
+        bg_width, bg_height = background.size
+        
+        # 제품 이미지 크기 가져오기
+        product_width, product_height = product.size
+        
+        # 먼저 type_b 형태로 아래 두 제품 이미지를 배치
+        background_with_two_products = paste_to_background_type_b(background, product, margin)
+
+        # 중앙 상단에 위치할 제품 이미지의 오프셋 계산
+        center_offset_x = (bg_width - product_width) // 2
+        center_offset_y = ((bg_height - product_height) // 2) + top_margin
+        
+        if center_offset_y < 0:
+            raise ValueError("Background is too small to fit three product images with the specified top margin.")
+        
+        # 세 번째 제품 이미지 배경에 합성 (중앙 상단)
+        background_with_two_products.paste(product, (center_offset_x, center_offset_y), mask=product)
+        
+        # 결과 이미지 저장 및 반환
+        return background_with_two_products
+    
+    except Exception as e:
+        print(f"Failed to paste product images to background: {e}")
+        return None
+    
+def create_zip_file(images: list, zip_filename: str = "images.zip") -> bytes:
+    # 메모리 내에서 ZIP 파일 생성
+    zip_buffer = BytesIO()
+    
+    with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zipf:
+        for i, image in enumerate(images):
+            # 이미지를 메모리 버퍼에 저장
+            image_buffer = BytesIO()
+            image.save(image_buffer, format="PNG")
+            image_buffer.seek(0)
+            
+            # 버퍼 내용을 ZIP 파일에 추가
+            zipf.writestr(f"image_{i + 1}.png", image_buffer.getvalue())
+    
+    # ZIP 파일 데이터를 반환
+    zip_buffer.seek(0)
+    return zip_buffer.getvalue()
+
+def image_processing_single(background_image: Image.Image, product_image_url: str):
+    # 각종 설정 값
+    product_image_size = 650 # 배경이 제거된 제품 이미지의 크기
+    type_b_margin = 15
+    type_c_margin_1, type_c_margin_2 = 15, 45 # (1=가운데 두개의 마진, 2= 중앙 한개의 top 마진)
+    
+    # 이미지 다운로드
+    original_image = download_image(product_image_url)
+
+    # 이미지 누끼따기
+    removebg_image = remove_background(original_image)
+    
+    # 이미지 크롭
+    cropped_image = crop_image(removebg_image)
+    
+    # 크롭된 이미지 원하는 사이즈로 resize
+    resized_image = resize_image(cropped_image, product_image_size)
+    
+    # type_a 합성
+    type_a_image = paste_to_background_type_a(background_image.copy(), resized_image)
+    type_b_image = paste_to_background_type_b(background_image.copy(), resized_image, type_b_margin)
+    type_c_image = paste_to_background_type_c(background_image.copy(), resized_image, type_c_margin_1, type_c_margin_2)
+    
+    # 결과 이미지 반환
+    image_list = [type_a_image, type_b_image, type_c_image]
+    image_zip_file = create_zip_file(image_list)
+    
+    return image_list #, image_zip_file
+
+def image_processing_multi(background_image: Image.Image, product_image_url_list: list):
+    # 각종 설정 값
+    product_image_size = 650 # 배경이 제거된 제품 이미지의 크기
+    type_b_margin = 15
+    type_c_margin_1, type_c_margin_2 = 15, 45 # (1=가운데 두개의 마진, 2= 중앙 한개의 top 마진)
+    
+    for idx, product_image_url in enumerate(product_image_url_list):
+        # 이미지 다운로드
+        original_image = download_image(product_image_url)
+
+        # 이미지 누끼따기
+        removebg_image = remove_background(original_image)
+        
+        # 이미지 크롭
+        cropped_image = crop_image(removebg_image)
+        
+        # 크롭된 이미지 원하는 사이즈로 resize
+        resized_image = resize_image(cropped_image, product_image_size)
+        
+        # type_a 합성
+        type_a_image = paste_to_background_type_a(background_image.copy(), resized_image)
+        type_b_image = paste_to_background_type_b(background_image.copy(), resized_image, type_b_margin)
+        type_c_image = paste_to_background_type_c(background_image.copy(), resized_image, type_c_margin_1, type_c_margin_2)
+        
+
+with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+    with gr.Row():
+        background_image = gr.Image(label="Background Image", type="pil")
+        with gr.Tab("Single"):
+            link = gr.Textbox(label="Image URL")
+            btn_single = gr.Button("Generate Images")
+        with gr.Tab("Multi"):
+            links = gr.File(label="Image URLs (.txt file)")
+            btn_multi = gr.Button("Generate Images")
+    
+    with gr.Row():
+        preview = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery", columns=[3], rows=[1], object_fit="contain", height="auto")
+        output_zip = gr.File(label="Download Result Zip File")
+        
+    # evnets
+    btn_single.click(fn=image_processing_single, inputs=[background_image, link], outputs=[preview], api_name="image_processing")
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()

links.txt

@@ -0,0 +1,10 @@
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/drb/drb00370/v/67.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/cgn/cgn01206/l/73.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/sre/sre01256/l/96.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/lex/lex19936/v/115.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/cey/cey66577/v/6.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/nor/nor01844/v/39.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/swv/swv06072/v/8.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/age/age00855/v/40.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/nhi/nhi03515/v/41.jpg,
+https://cloudinary.images-iherb.com/image/upload/f_auto,q_auto:eco/images/nhi/nhi03512/v/49.jpg,

requirements.txt

@@ -0,0 +1,82 @@
+aiofiles==23.2.1
+annotated-types==0.7.0
+anyio==4.6.0
+attrs==24.2.0
+certifi==2024.8.30
+charset-normalizer==3.3.2
+click==8.1.7
+coloredlogs==15.0.1
+contourpy==1.3.0
+cycler==0.12.1
+fastapi==0.115.0
+ffmpy==0.4.0
+filelock==3.16.1
+flatbuffers==24.3.25
+fonttools==4.53.1
+fsspec==2024.9.0
+gradio==4.44.0
+gradio_client==1.3.0
+h11==0.14.0
+httpcore==1.0.5
+httpx==0.27.2
+huggingface-hub==0.25.0
+humanfriendly==10.0
+idna==3.10
+imageio==2.35.1
+importlib_resources==6.4.5
+Jinja2==3.1.4
+jsonschema==4.23.0
+jsonschema-specifications==2023.12.1
+kiwisolver==1.4.7
+lazy_loader==0.4
+llvmlite==0.43.0
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.9.2
+mdurl==0.1.2
+mpmath==1.3.0
+networkx==3.3
+numba==0.60.0
+numpy==2.0.2
+onnxruntime==1.19.2
+opencv-python-headless==4.10.0.84
+orjson==3.10.7
+packaging==24.1
+pandas==2.2.3
+pillow==10.4.0
+platformdirs==4.3.6
+pooch==1.8.2
+protobuf==5.28.2
+pydantic==2.9.2
+pydantic_core==2.23.4
+pydub==0.25.1
+Pygments==2.18.0
+PyMatting==1.1.12
+pyparsing==3.1.4
+python-dateutil==2.9.0.post0
+python-multipart==0.0.9
+pytz==2024.2
+PyYAML==6.0.2
+referencing==0.35.1
+rembg==2.0.59
+requests==2.32.3
+rich==13.8.1
+rpds-py==0.20.0
+ruff==0.6.6
+scikit-image==0.24.0
+scipy==1.14.1
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.1
+starlette==0.38.5
+sympy==1.13.3
+tifffile==2024.9.20
+tomlkit==0.12.0
+tqdm==4.66.5
+typer==0.12.5
+typing_extensions==4.12.2
+tzdata==2024.1
+urllib3==2.2.3
+uvicorn==0.30.6
+websockets==12.0