| import spaces |
| import gradio as gr |
| import subprocess |
| from PIL import Image,ImageEnhance,ImageFilter |
| import json |
| import numpy as np |
| from skimage.exposure import match_histograms |
|
|
| import mp_box |
| ''' |
| Face landmark detection based Face Detection. |
| https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker |
| from model card |
| https://storage.googleapis.com/mediapipe-assets/MediaPipe%20BlazeFace%20Model%20Card%20(Short%20Range).pdf |
| Licensed Apache License, Version 2.0 |
| Train with google's dataset(more detail see model card) |
| |
| Not Face Detector based |
| https://ai.google.dev/edge/mediapipe/solutions/vision/face_detector |
| |
| Bacause this is part of getting-landmark program and need control face edge. |
| So I don't know which one is better.never compare these. |
| ''' |
|
|
| def color_match(base_image,cropped_image): |
| reference = np.array(base_image) |
| target =np.array(cropped_image) |
| matched = match_histograms(target, reference,channel_axis=-1) |
| return Image.fromarray(matched) |
|
|
| def select_box(boxes,box_type): |
| if box_type == "type-3": |
| box = boxes[2] |
| elif box_type =="type-2": |
| box = boxes[1] |
| elif box_type =="type-1": |
| box = boxes[0] |
| else: |
| box=[0,0,image.size[0],image.size[1]] |
| box_width = box[2] |
| box_height = box[3] |
| box = mp_box.xywh_to_xyxy(box) |
| return box,box_width,box_height |
|
|
| def resize_image_in_box(image,box_width,box_height,keep_aspect=True,resampling=None): |
|
|
| aspect_ratio = image.width / image.height |
| if box_width / box_height >= aspect_ratio: |
| new_width = int(box_height * aspect_ratio) |
| new_height = box_height |
| else: |
| new_width = box_width |
| new_height = int(box_width / aspect_ratio) |
|
|
|
|
| if resampling == None: |
| image_area = image.width * image.height |
| if box_width * box_height > image_area: |
| resampling = Image.Resampling.BICUBIC |
| else: |
| resampling = Image.Resampling.LANCZOS |
|
|
| resized = image.resize((new_width,new_height),resampling) |
| offset_x = int((box_width -new_width)/2) |
| offset_y = int((box_height -new_height)/2) |
| return resized,offset_x,offset_y |
|
|
|
|
| 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)): |
| |
| if image == None: |
| raise gr.Error("Need Image") |
|
|
| |
| image_width,image_height = image.size |
| boxes,mp_image,face_landmarker_result = mp_box.mediapipe_to_box(image) |
| box,box_width,box_height = select_box(boxes,box_type) |
|
|
| |
| if replace_image!=None: |
| print("replace mode") |
|
|
| if replace_image_need_crop: |
| replace_boxes,mp_image,face_landmarker_result = mp_box.mediapipe_to_box(replace_image) |
| replace_box,replace_box_width,replace_box_height = select_box(replace_boxes,box_type) |
|
|
| keep_aspect = True |
| |
| if fill_color_mode: |
| if replace_image_need_crop: |
| cropped = replace_image.crop(replace_box) |
| cropped,off_x,off_y = resize_image_in_box(cropped,box_width,box_height,keep_aspect) |
| else: |
| cropped = replace_image.crop(box) |
| off_x = int((box_width -cropped.width)/2) |
| off_y = int((box_height -cropped.height)/2) |
| |
| if match_color: |
| cropped = color_match(image.crop(box),cropped) |
| |
| image.paste(cropped,[box[0]+off_x,box[1]+off_y]) |
| return image |
| else: |
| |
| if margin_percent>0: |
| h_margin = int(box_width*margin_percent/100) |
| v_margin = int(box_height*margin_percent/100) |
|
|
| box[0] = max(0,box[0]-h_margin) |
| box[1] = max(0,box[1]-v_margin) |
| box[2] = min(image_width-1,box[2]+h_margin) |
| box[3] = min(image_height-1,box[3]+v_margin) |
| box_width = box[2]-box[0] |
| box_height = box[3]-box[1] |
|
|
| if replace_image_need_crop: |
| replace_image = replace_image.crop(replace_box) |
|
|
| |
| |
| replace_resized,off_x,off_y = resize_image_in_box(replace_image,box_width,box_height,keep_aspect) |
| if match_color: |
| replace_resized = color_match(image.crop(box),replace_resized) |
| |
| image.paste(replace_resized,[box[0]+off_x,box[1]+off_y]) |
| return image |
|
|
|
|
| |
| if margin_percent>0: |
| h_margin = int(box_width*margin_percent/100) |
| v_margin = int(box_height*margin_percent/100) |
|
|
| box[0] = max(0,box[0]-h_margin) |
| box[1] = max(0,box[1]-v_margin) |
| box[2] = min(image_width-1,box[2]+h_margin) |
| box[3] = min(image_height-1,box[3]+v_margin) |
| |
| |
| if fill_color_mode: |
| |
| color_map={ |
| "black":[0,0,0,1], |
| "white":[255,255,255,1], |
| "gray":[127,127,127,1], |
| "red":[255,0,0,1], |
| "brown":[92,33,31,1], |
| "pink":[255,192,203,1], |
| } |
| if fill_color == "custom": |
| color_value = custom_color.strip("rgba()").split(",") |
| color_value[0] = int(float(color_value[0])) |
| color_value[1] = int(float(color_value[1])) |
| color_value[2] = int(float(color_value[2])) |
| else: |
| color_value = color_map[fill_color] |
|
|
| cropped = image.crop(box) |
|
|
| img = Image.new('RGBA', image.size, (color_value[0], color_value[1], color_value[2])) |
| img.paste(cropped,[box[0],box[1]]) |
| return img |
| else: |
| |
| cropped = image.crop(box) |
| resized = resize_image_by_max_dimension(cropped,image_size) |
| |
| filter_map={ |
| "None":None, |
| "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 |
| } |
|
|
| if filter_value not in filter_map: |
| raise gr.Error(f"filter {filter_value} not found") |
| |
| if filter_value != "None": |
| |
| |
| |
| enhancer = ImageEnhance.Sharpness(resized) |
| resized = resized.filter(filter_map[filter_value]) |
| |
|
|
|
|
| return resized |
|
|
|
|
| def resize_image_by_max_dimension(image, max_size, resampling=Image.Resampling.BICUBIC): |
| image_width, image_height = image.size |
| |
| max_dimension = max(image_width, image_height) |
| |
| ratio = max_size / max_dimension |
| |
| new_width = int(image_width * ratio) |
| new_height = int(image_height * ratio) |
| |
| return image.resize((new_width, new_height), resampling) |
| |
|
|
| def read_file(file_path: str) -> str: |
| """read the text of target file |
| """ |
| with open(file_path, 'r', encoding='utf-8') as f: |
| content = f.read() |
|
|
| return content |
|
|
| css=""" |
| #col-left { |
| margin: 0 auto; |
| max-width: 640px; |
| } |
| #col-right { |
| margin: 0 auto; |
| max-width: 640px; |
| } |
| .grid-container { |
| display: flex; |
| align-items: center; |
| justify-content: center; |
| gap:10px |
| } |
| |
| .image { |
| width: 128px; |
| height: 128px; |
| object-fit: cover; |
| } |
| |
| .text { |
| font-size: 16px; |
| } |
| """ |
|
|
| |
| def update_button_label(image): |
| if image == None: |
| print("none replace") |
| return gr.Button(visible=True),gr.Button(visible=False),gr.Row(visible=True),gr.Row(visible=True) |
| else: |
| return gr.Button(visible=False),gr.Button(visible=True),gr.Row(visible=False),gr.Row(visible=False) |
| |
| def update_visible(fill_color_mode,image): |
| if image != None: |
| return gr.Row(visible=False),gr.Row(visible=False) |
| |
| if fill_color_mode: |
| return gr.Row(visible=False),gr.Row(visible=True) |
| else: |
| return gr.Row(visible=True),gr.Row(visible=False) |
| |
| with gr.Blocks(css=css, elem_id="demo-container") as demo: |
| with gr.Column(): |
| gr.HTML(read_file("demo_header.html")) |
| gr.HTML(read_file("demo_tools.html")) |
| with gr.Row(): |
| with gr.Column(): |
| image = gr.Image(sources=['upload','clipboard'],image_mode='RGB',elem_id="image_upload", type="pil", label="Upload") |
| box_type = gr.Dropdown(label="box-type",value="type-3",choices=["type-1","type-2","type-3"]) |
| with gr.Row(elem_id="prompt-container", equal_height=False): |
| with gr.Row(): |
| btn1 = gr.Button("Face Crop", elem_id="run_button",variant="primary") |
| btn2 = gr.Button("Face Replace", elem_id="run_button2",variant="primary",visible=False) |
| |
| replace_image = gr.Image(sources=['upload','clipboard'],image_mode='RGB',elem_id="replace_upload", type="pil", label="replace image") |
| replace_image_need_crop = gr.Checkbox(label="Replace image need crop",value=False) |
| |
| with gr.Accordion(label="Advanced Settings", open=False): |
| with gr.Row(equal_height=True): |
| fill_color_mode = gr.Checkbox(label="Fill Color Mode/No Resize",value=False) |
| match_color = gr.Checkbox(label="Match Color",value=True,info="skimage match_histograms") |
| margin_percent = gr.Slider( |
| label="Margin percent",info = "add extra space", |
| minimum=0, |
| maximum=200, |
| step=1, |
| value=0, |
| interactive=True) |
| |
| |
| row1 = gr.Row(equal_height=True) |
| row2 = gr.Row(equal_height=True,visible=False) |
| fill_color_mode.change(update_visible,[fill_color_mode,replace_image],[row1,row2]) |
| with row1: |
| image_size = gr.Slider( |
| label="Image Size",info = "cropped face size", |
| minimum=8, |
| maximum=2048, |
| step=1, |
| value=1024, |
| interactive=True) |
|
|
| |
|
|
| |
| filter_value = gr.Dropdown(label="Filter",value="None",choices=["Blur","Smooth More","Smooth","None","Sharpen","Edge Enhance","Edge Enhance More"]) |
| with row2: |
| |
| fill_color = gr.Dropdown(label="fill color",choices=["black","white","gray","red","brown","pink","custom"],value="gray") |
| custom_color = gr.ColorPicker(label="custom color",value="rgba(250, 218, 205, 1)") |
| |
| replace_image.change(update_button_label,replace_image,[btn1,btn2,row1,row2]) |
| with gr.Column(): |
| image_out = gr.Image(label="Output", elem_id="output-img") |
| |
| |
| |
| |
|
|
| |
| gr.on( |
| [btn1.click,btn2.click], |
| 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' |
| ) |
| gr.Examples( |
| examples =["examples/00004200.jpg","examples/00003245_00.jpg","examples/00005259.jpg","examples/00018022.jpg","examples/img-above.jpg","examples/img-below.jpg","examples/img-side.jpg"], |
| inputs=[image] |
| ) |
| gr.HTML(read_file("demo_footer.html")) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
