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#!/usr/bin/env python
from __future__ import annotations
import pathlib
import gradio as gr
import mediapipe as mp
import numpy as np
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_face_mesh = mp.solutions.face_mesh
TITLE = "MediaPipe Face Mesh"
DESCRIPTION = "https://google.github.io/mediapipe/"
def run(
image: np.ndarray,
max_num_faces: int,
min_detection_confidence: float,
show_tesselation: bool,
show_contours: bool,
show_irises: bool,
) -> np.ndarray:
with mp_face_mesh.FaceMesh(
static_image_mode=True,
max_num_faces=max_num_faces,
refine_landmarks=True,
min_detection_confidence=min_detection_confidence,
) as face_mesh:
results = face_mesh.process(image)
res = image[:, :, ::-1].copy()
if results.multi_face_landmarks is not None:
for face_landmarks in results.multi_face_landmarks:
if show_tesselation:
mp_drawing.draw_landmarks(
image=res,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_TESSELATION,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_tesselation_style(),
)
if show_contours:
mp_drawing.draw_landmarks(
image=res,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_CONTOURS,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style(),
)
if show_irises:
mp_drawing.draw_landmarks(
image=res,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_IRISES,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_iris_connections_style(),
)
return res[:, :, ::-1]
image_paths = sorted(pathlib.Path("images").rglob("*.jpg"))
examples = [[path, 5, 0.5, True, True, True] for path in image_paths]
demo = gr.Interface(
fn=run,
inputs=[
gr.Image(label="Input", type="numpy"),
gr.Slider(label="Max Number of Faces", minimum=0, maximum=10, step=1, value=5),
gr.Slider(label="Minimum Detection Confidence", minimum=0, maximum=1, step=0.05, value=0.5),
gr.Checkbox(label="Show Tesselation", value=True),
gr.Checkbox(label="Show Contours", value=True),
gr.Checkbox(label="Show Irises", value=True),
],
outputs=gr.Image(label="Output"),
examples=examples,
title=TITLE,
description=DESCRIPTION,
)
if __name__ == "__main__":
demo.queue().launch()
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