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96 lines
3.5 KiB
Python
96 lines
3.5 KiB
Python
import click
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import cv2
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import inspireface as ifac
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from inspireface.param import *
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import numpy as np
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@click.command()
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@click.argument("resource_path")
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@click.argument('source')
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@click.option('--show', is_flag=True, help='Display the video stream or video file in a window.')
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def case_face_tracker_from_video(resource_path, source, show):
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"""
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Launch a face tracking process from a video source. The 'source' can either be a webcam index (0, 1, ...)
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or a path to a video file. Use the --show option to display the video.
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Args:
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resource_path (str): Path to the resource directory for face tracking algorithms.
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source (str): Webcam index or path to the video file.
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show (bool): If set, the video will be displayed in a window.
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"""
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# Initialize the face tracker or other resources.
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print(f"Initializing with resources from: {resource_path}")
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# Step 1: Initialize the SDK and load the algorithm resource files.
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ret = ifac.launch(resource_path)
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assert ret, "Launch failure. Please ensure the resource path is correct."
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# Optional features, loaded during session creation based on the modules specified.
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opt = HF_ENABLE_NONE
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session = ifac.InspireFaceSession(opt, HF_DETECT_MODE_LIGHT_TRACK) # Use video mode
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# Determine if the source is a digital webcam index or a video file path.
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try:
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source_index = int(source) # Try to convert source to an integer.
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cap = cv2.VideoCapture(source_index)
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print(f"Using webcam at index {source_index}.")
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except ValueError:
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# If conversion fails, treat source as a file path.
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cap = cv2.VideoCapture(source)
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print(f"Opening video file at {source}.")
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if not cap.isOpened():
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print("Error: Could not open video source.")
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return
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# Main loop to process video frames.
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while True:
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ret, frame = cap.read()
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if not ret:
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break # Exit loop if no more frames or error occurs.
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# Process frame here (e.g., face detection/tracking).
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faces = session.face_detection(frame)
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for idx, face in enumerate(faces):
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print(f"{'==' * 20}")
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print(f"idx: {idx}")
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# Print Euler angles of the face.
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print(f"roll: {face.roll}, yaw: {face.yaw}, pitch: {face.pitch}")
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# Get face bounding box
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x1, y1, x2, y2 = face.location
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# Calculate center, size, and angle
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center = ((x1 + x2) / 2, (y1 + y2) / 2)
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size = (x2 - x1, y2 - y1)
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angle = face.roll
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# Get rotation matrix
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rotation_matrix = cv2.getRotationMatrix2D(center, angle, 1.0)
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# Apply rotation to the bounding box corners
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rect = ((center[0], center[1]), (size[0], size[1]), angle)
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box = cv2.boxPoints(rect)
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box = box.astype(int)
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# Draw the rotated bounding box
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cv2.drawContours(frame, [box], 0, (100, 180, 29), 2)
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# Draw landmarks
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lmk = session.get_face_dense_landmark(face)
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for x, y in lmk.astype(int):
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cv2.circle(frame, (x, y), 0, (220, 100, 0), 2)
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if show:
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cv2.imshow("Face Tracker", frame)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break # Exit loop if 'q' is pressed.
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# Cleanup: release video capture and close any open windows.
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cap.release()
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cv2.destroyAllWindows()
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print("Released all resources and closed windows.")
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if __name__ == '__main__':
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case_face_tracker_from_video()
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