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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()
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