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import spaces |
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import gradio as gr |
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import subprocess |
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from PIL import Image,ImageEnhance,ImageFilter |
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import json |
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import numpy as np |
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from skimage.exposure import match_histograms |
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import mp_box |
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''' |
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Face landmark detection based Face Detection. |
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https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker |
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from model card |
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https://storage.googleapis.com/mediapipe-assets/MediaPipe%20BlazeFace%20Model%20Card%20(Short%20Range).pdf |
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Licensed Apache License, Version 2.0 |
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Train with google's dataset(more detail see model card) |
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Not Face Detector based |
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https://ai.google.dev/edge/mediapipe/solutions/vision/face_detector |
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Bacause this is part of getting-landmark program and need control face edge. |
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So I don't know which one is better.never compare these. |
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''' |
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def color_match(base_image,cropped_image): |
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reference = np.array(base_image) |
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target =np.array(cropped_image) |
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matched = match_histograms(target, reference,channel_axis=-1) |
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return Image.fromarray(matched) |
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def select_box(boxes,box_type): |
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if box_type == "type-3": |
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box = boxes[2] |
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elif box_type =="type-2": |
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box = boxes[1] |
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elif box_type =="type-1": |
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box = boxes[0] |
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else: |
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box=[0,0,image.size[0],image.size[1]] |
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box_width = box[2] |
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box_height = box[3] |
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box = mp_box.xywh_to_xyxy(box) |
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return box,box_width,box_height |
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def process_images(image,replace_image=None,replace_image_need_crop=False,box_type="type-3",fill_color_mode=False,fill_color="black",custom_color="rgba(255,255,255,1)",image_size=1024,margin_percent=0,filter_value="None",match_color=True,progress=gr.Progress(track_tqdm=True)): |
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if image == None: |
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raise gr.Error("Need Image") |
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image_width,image_height = image.size |
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boxes,mp_image,face_landmarker_result = mp_box.mediapipe_to_box(image) |
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box,box_width,box_height = select_box(boxes,box_type) |
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if replace_image!=None: |
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print("replace mode") |
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if replace_image_need_crop: |
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replace_boxes,mp_image,face_landmarker_result = mp_box.mediapipe_to_box(replace_image) |
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replace_box,replace_box_width,replace_box_height = select_box(replace_boxes,box_type) |
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if fill_color_mode: |
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if replace_image_need_crop: |
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cropped = replace_image.crop(replace_box) |
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cropped.resize((box_width,box_height)) |
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else: |
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cropped = replace_image.crop(box) |
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if match_color: |
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cropped = color_match(image.crop(box),cropped) |
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image.paste(cropped,[box[0],box[1]]) |
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return image |
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else: |
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if margin_percent>0: |
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h_margin = int(box_width*margin_percent/100) |
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v_margin = int(box_height*margin_percent/100) |
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box[0] = max(0,box[0]-h_margin) |
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box[1] = max(0,box[1]-v_margin) |
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box[2] = min(image_width-1,box[2]+h_margin) |
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box[3] = min(image_height-1,box[3]+v_margin) |
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box_width = box[2]-box[0] |
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box_height = box[3]-box[1] |
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if replace_image_need_crop: |
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replace_image = replace_image.crop(replace_box) |
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replace_resized = replace_image.resize((box_width,box_height),Image.Resampling.LANCZOS) |
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if match_color: |
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replace_resized = color_match(image.crop(box),replace_resized) |
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image.paste(replace_resized,[box[0],box[1]]) |
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return image |
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if margin_percent>0: |
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h_margin = int(box_width*margin_percent/100) |
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v_margin = int(box_height*margin_percent/100) |
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box[0] = max(0,box[0]-h_margin) |
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box[1] = max(0,box[1]-v_margin) |
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box[2] = min(image_width-1,box[2]+h_margin) |
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box[3] = min(image_height-1,box[3]+v_margin) |
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if fill_color_mode: |
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color_map={ |
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"black":[0,0,0,1], |
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"white":[255,255,255,1], |
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"gray":[127,127,127,1], |
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"red":[255,0,0,1], |
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"brown":[92,33,31,1], |
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"pink":[255,192,203,1], |
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} |
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if fill_color == "custom": |
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color_value = custom_color.strip("rgba()").split(",") |
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color_value[0] = int(float(color_value[0])) |
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color_value[1] = int(float(color_value[1])) |
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color_value[2] = int(float(color_value[2])) |
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else: |
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color_value = color_map[fill_color] |
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cropped = image.crop(box) |
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img = Image.new('RGBA', image.size, (color_value[0], color_value[1], color_value[2])) |
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img.paste(cropped,[box[0],box[1]]) |
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return img |
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else: |
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cropped = image.crop(box) |
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resized = resize_image_by_max_dimension(cropped,image_size) |
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filter_map={ |
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"None":None, |
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"Blur":ImageFilter.BLUR,"Smooth More":ImageFilter.SMOOTH_MORE,"Smooth":ImageFilter.SMOOTH,"Sharpen":ImageFilter.SHARPEN,"Edge Enhance":ImageFilter.EDGE_ENHANCE,"Edge Enhance More":ImageFilter.EDGE_ENHANCE_MORE |
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} |
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if filter_value not in filter_map: |
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raise gr.Error(f"filter {filter_value} not found") |
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if filter_value != "None": |
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enhancer = ImageEnhance.Sharpness(resized) |
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resized = resized.filter(filter_map[filter_value]) |
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return resized |
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def resize_image_by_max_dimension(image, max_size, resampling=Image.Resampling.BICUBIC): |
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image_width, image_height = image.size |
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max_dimension = max(image_width, image_height) |
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ratio = max_size / max_dimension |
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new_width = int(image_width * ratio) |
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new_height = int(image_height * ratio) |
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return image.resize((new_width, new_height), resampling) |
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def read_file(file_path: str) -> str: |
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"""read the text of target file |
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""" |
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with open(file_path, 'r', encoding='utf-8') as f: |
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content = f.read() |
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return content |
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css=""" |
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#col-left { |
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margin: 0 auto; |
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max-width: 640px; |
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} |
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#col-right { |
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margin: 0 auto; |
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max-width: 640px; |
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} |
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.grid-container { |
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display: flex; |
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align-items: center; |
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justify-content: center; |
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gap:10px |
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} |
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.image { |
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width: 128px; |
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height: 128px; |
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object-fit: cover; |
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} |
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.text { |
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font-size: 16px; |
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} |
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""" |
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def update_button_label(image): |
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if image == None: |
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print("none replace") |
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return gr.Button(visible=True),gr.Button(visible=False),gr.Row(visible=True),gr.Row(visible=True) |
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else: |
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return gr.Button(visible=False),gr.Button(visible=True),gr.Row(visible=False),gr.Row(visible=False) |
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def update_visible(fill_color_mode,image): |
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if image != None: |
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return gr.Row(visible=False),gr.Row(visible=False) |
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if fill_color_mode: |
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return gr.Row(visible=False),gr.Row(visible=True) |
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else: |
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return gr.Row(visible=True),gr.Row(visible=False) |
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with gr.Blocks(css=css, elem_id="demo-container") as demo: |
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with gr.Column(): |
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gr.HTML(read_file("demo_header.html")) |
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gr.HTML(read_file("demo_tools.html")) |
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with gr.Row(): |
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with gr.Column(): |
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image = gr.Image(sources=['upload','clipboard'],image_mode='RGB',elem_id="image_upload", type="pil", label="Upload") |
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box_type = gr.Dropdown(label="box-type",value="type-3",choices=["type-1","type-2","type-3"]) |
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with gr.Row(elem_id="prompt-container", equal_height=False): |
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with gr.Row(): |
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btn1 = gr.Button("Face Crop", elem_id="run_button",variant="primary") |
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btn2 = gr.Button("Face Replace", elem_id="run_button2",variant="primary",visible=False) |
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replace_image = gr.Image(sources=['upload','clipboard'],image_mode='RGB',elem_id="replace_upload", type="pil", label="replace image") |
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replace_image_need_crop = gr.Checkbox(label="Replace image need crop",value=False) |
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with gr.Accordion(label="Advanced Settings", open=False): |
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with gr.Row(equal_height=True): |
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fill_color_mode = gr.Checkbox(label="Fill Color Mode/No Resize",value=False) |
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match_color = gr.Checkbox(label="Match Color",value=True) |
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margin_percent = gr.Slider( |
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label="Margin percent",info = "add extra space", |
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minimum=0, |
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maximum=200, |
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step=1, |
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value=0, |
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interactive=True) |
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row1 = gr.Row(equal_height=True) |
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row2 = gr.Row(equal_height=True,visible=False) |
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fill_color_mode.change(update_visible,[fill_color_mode,replace_image],[row1,row2]) |
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with row1: |
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image_size = gr.Slider( |
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label="Image Size",info = "cropped face size", |
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minimum=8, |
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maximum=2048, |
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step=1, |
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value=1024, |
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interactive=True) |
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filter_value = gr.Dropdown(label="Filter",value="None",choices=["Blur","Smooth More","Smooth","None","Sharpen","Edge Enhance","Edge Enhance More"]) |
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with row2: |
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fill_color = gr.Dropdown(label="fill color",choices=["black","white","gray","red","brown","pink","custom"],value="gray") |
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custom_color = gr.ColorPicker(label="custom color",value="rgba(250, 218, 205, 1)") |
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replace_image.change(update_button_label,replace_image,[btn1,btn2,row1,row2]) |
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with gr.Column(): |
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image_out = gr.Image(label="Output", elem_id="output-img") |
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gr.on( |
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[btn1.click,btn2.click], |
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fn=process_images, inputs=[image,replace_image,replace_image_need_crop,box_type,fill_color_mode,fill_color,custom_color,image_size,margin_percent,filter_value,match_color], outputs =[image_out], api_name='infer' |
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) |
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gr.Examples( |
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examples =["examples/00004200.jpg"], |
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inputs=[image] |
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) |
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gr.HTML(read_file("demo_footer.html")) |
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if __name__ == "__main__": |
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demo.launch() |
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