import spaces import gradio as gr ''' ''' from gradio_utils import clear_old_files,read_file from face_mesh_spinning import process_face_mesh_spinning from mp_estimate import mean_std_label,estimate_horizontal,estimate_vertical,estimate_horizontal_points,estimate_vertical_points def process_images(image,draw_type,center_scaleup,animation_direction, z_multiply,inner_eyes,inner_mouth, progress=gr.Progress(track_tqdm=True)): clear_old_files() if image==None: raise gr.Error("need image") result,face_landmarker_result,rotated_points = process_face_mesh_spinning(image,draw_type,center_scaleup,animation_direction,z_multiply,inner_eyes,inner_mouth) return result 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; } """ from glibvision.cv2_utils import pil_to_bgr_image,copy_image from mp_utils import extract_landmark,get_pixel_cordinate import numpy as np # TODO move mp_util def extract_landmark_double_check(numpy_image,double_check=True,center_index=4,extract_matrix=True):#4 is nose-tip mp_image,face_landmarker_result = extract_landmark(numpy_image,"face_landmarker.task",0,0,extract_matrix) h,w = numpy_image.shape[:2] second_mp_image,first_landmarker_result = None,None numpy_view = mp_image.numpy_view() if double_check: root_cordinate = get_pixel_cordinate(face_landmarker_result.face_landmarks,center_index,w,h) diff_center_x = int(w/2 - root_cordinate[0]) diff_center_y = int(h/2 - root_cordinate[1]) base = np.zeros_like(numpy_view) copy_image(base,numpy_view,diff_center_x,diff_center_y) first_landmarker_result = face_landmarker_result second_mp_image,face_landmarker_result = extract_landmark(base,"face_landmarker.task",0,0,extract_matrix) return mp_image,face_landmarker_result,second_mp_image,first_landmarker_result #css=css, from scipy.spatial.transform import Rotation as R def calculate_angle(image,double_check,ignore_x,order): cv2_base_image = pil_to_bgr_image(image) mp_image,face_landmarker_result,_,_ = extract_landmark_double_check(cv2_base_image,double_check) if len(face_landmarker_result.facial_transformation_matrixes)>0: transformation_matrix=face_landmarker_result.facial_transformation_matrixes[0] rotation_matrix, translation_vector = transformation_matrix[:3, :3],transformation_matrix[:3, 3] r = R.from_matrix(rotation_matrix) euler_angles = r.as_euler(order, degrees=True) label = f"Mediapipe Euler yxz: {euler_angles}" if ignore_x: euler_angles[1]=0 result = [label,0,0,0] for i,ch in enumerate(order.lower()): if ch == "x": result[1] = -euler_angles[i] elif ch == "y": result[2] = euler_angles[i] elif ch == "z": result[3] = euler_angles[i] return result return label,-euler_angles[1],euler_angles[0],euler_angles[2] return "",0,0,0 def change_animation(animation): if animation: return gr.Column(visible=True),gr.Column(visible=False) else: return gr.Column(visible=False),gr.Column(visible=True) 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(height=800,sources=['upload','clipboard'],image_mode='RGB',elem_id="image_upload", type="pil", label="Image") with gr.Row(elem_id="prompt-container", equal_height=False): with gr.Row(): btn = gr.Button("Rotate Mesh", elem_id="run_button",variant="primary") with gr.Accordion(label="Advanced Settings", open=True): draw_type = gr.Radio(label="Draw type",choices=["Dot","Line","Line+Fill","Image"],value="Line",info="making image animation,take over 60 sec and limited frame only") with gr.Row( equal_height=True): inner_eyes=gr.Checkbox(label="Inner Eyes",value=True) inner_mouth=gr.Checkbox(label="Inner Mouth",value=True) with gr.Row( equal_height=True): center_scaleup = gr.Checkbox(label="ScaleUp/Fit",value=True,info="center is nose-tip,Zoomed face usually make small") z_multiply = gr.Slider(info="Nose height", label="Depth-Multiply", minimum=0.1, maximum=1.5, step=0.01, value=0.8) animation_column = gr.Column(visible=True) with animation_column: with gr.Row( equal_height=True): animation_direction = gr.Radio(label="Animation Direction",choices=["X","Y","Z"],value="Y") with gr.Column(): result_image = gr.Image(height=760,label="Result", elem_id="output-animation",image_mode='RGBA') btn.click(fn=process_images, inputs=[image,draw_type,center_scaleup,animation_direction, z_multiply,inner_eyes,inner_mouth, ],outputs=[result_image, ] ,api_name='infer') example_images = [ ["examples/02316230.jpg","examples/02316230.webp"], ["examples/00003245_00.jpg","examples/00003245_00.webp"], ["examples/00827009.jpg","examples/00827009.webp"], ["examples/00002062.jpg","examples/00002062.webp"], ["examples/00824008.jpg","examples/00824008.webp"], ["examples/00825000.jpg","examples/00825000.webp"], ["examples/00826007.jpg","examples/00826007.webp"], ["examples/00824006.jpg","examples/00824006.webp"], ["examples/00002200.jpg","examples/00002200.webp"], ["examples/00005259.jpg","examples/00005259.webp"], ["examples/00018022.jpg","examples/00018022.webp"], ["examples/img-above.jpg","examples/img-above.webp"], ["examples/00100265.jpg","examples/00100265.webp"], ["examples/00039259.jpg","examples/00039259.webp"], ] example1=gr.Examples( examples = example_images,label="Image", inputs=[image,result_image],examples_per_page=8 ) gr.HTML(read_file("demo_footer.html")) if __name__ == "__main__": demo.launch()