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import cv2
import mediapipe as mp
import numpy as np
import gradio as gr
# Initialize Mediapipe solutions
mp_hands = mp.solutions.hands
mp_face_mesh = mp.solutions.face_mesh
mp_drawing = mp.solutions.drawing_utils
# Function to process and draw landmarks on the input image
def process_image(input_image):
# Convert input image to RGB for Mediapipe
rgb_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
# Initialize Hands and Face Mesh models
with mp_hands.Hands(static_image_mode=True, min_detection_confidence=0.5) as hands, \
mp_face_mesh.FaceMesh(static_image_mode=True, min_detection_confidence=0.5) as face_mesh:
# Process the image for hands
hand_results = hands.process(rgb_image)
# Process the image for face mesh
face_results = face_mesh.process(rgb_image)
# Draw Hand Landmarks
if hand_results.multi_hand_landmarks:
for hand_landmarks in hand_results.multi_hand_landmarks:
mp_drawing.draw_landmarks(
input_image, hand_landmarks, mp_hands.HAND_CONNECTIONS,
mp_drawing.DrawingSpec(color=(121, 22, 76), thickness=2, circle_radius=4),
mp_drawing.DrawingSpec(color=(250, 44, 250), thickness=2, circle_radius=2)
)
# Draw Face Mesh Landmarks
if face_results.multi_face_landmarks:
for face_landmarks in face_results.multi_face_landmarks:
mp_drawing.draw_landmarks(
input_image, face_landmarks, mp_face_mesh.FACEMESH_TESSELATION,
mp_drawing.DrawingSpec(color=(80, 110, 10), thickness=1, circle_radius=1),
mp_drawing.DrawingSpec(color=(80, 256, 121), thickness=1, circle_radius=1)
)
return input_image
# Gradio interface
def gradio_interface(image):
# Convert Gradio PIL image to OpenCV format
image = np.array(image)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# Process the image to detect landmarks
processed_image = process_image(image)
# Convert the processed image back to RGB for display in Gradio
processed_image = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
return processed_image
# Define Gradio app
iface = gr.Interface(
fn=gradio_interface,
inputs=gr.Image(type="pil"),
outputs=gr.Image(type="numpy"),
title="Face and Hand Landmarks Detection",
description="Upload an image or take a photo to detect face and hand landmarks using Mediapipe and OpenCV."
)
# Launch Gradio app
if __name__ == "__main__":
iface.launch()
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