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https://github.com/ck-zhang/EyePy.git
synced 2025-12-31 08:20:20 -06:00
Extract video helpers; dedup camera/window loops
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ck-zhang
@@ -3,6 +3,7 @@ import cv2
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import numpy as np
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import os
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from eyetrax.utils.screen import get_screen_size
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from eyetrax.utils.video import camera, fullscreen, iter_frames
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from eyetrax.gaze import GazeEstimator
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from eyetrax.calibration import (
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run_9_point_calibration,
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@@ -51,10 +52,6 @@ def run_demo():
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kalman = None
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smoother = NoSmoother()
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cam_width, cam_height = 320, 240
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BORDER = 2
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MARGIN = 20
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if background_path and os.path.isfile(background_path):
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background = cv2.imread(background_path)
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background = cv2.resize(background, (screen_width, screen_height))
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@@ -62,96 +59,91 @@ def run_demo():
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background = np.zeros((screen_height, screen_width, 3), dtype=np.uint8)
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background[:] = (50, 50, 50)
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cv2.namedWindow("Gaze Estimation", cv2.WND_PROP_FULLSCREEN)
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cv2.setWindowProperty(
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"Gaze Estimation", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN
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)
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cap = cv2.VideoCapture(camera_index)
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prev_time = time.time()
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cam_width, cam_height = 320, 240
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BORDER = 2
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MARGIN = 20
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cursor_alpha = 0.0
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cursor_step = 0.05
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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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continue
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with camera(camera_index) as cap, fullscreen("Gaze Estimation"):
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prev_time = time.time()
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features, blink_detected = gaze_estimator.extract_features(frame)
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if features is not None and not blink_detected:
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gaze_point = gaze_estimator.predict(np.array([features]))[0]
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x, y = map(int, gaze_point)
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for frame in iter_frames(cap):
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features, blink_detected = gaze_estimator.extract_features(frame)
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x_pred, y_pred = smoother.step(x, y)
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contours = smoother.debug.get("contours", [])
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if features is not None and not blink_detected:
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gaze_point = gaze_estimator.predict(np.array([features]))[0]
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x, y = map(int, gaze_point)
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x_pred, y_pred = smoother.step(x, y)
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contours = smoother.debug.get("contours", [])
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cursor_alpha = min(cursor_alpha + cursor_step, 1.0)
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else:
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x_pred = y_pred = None
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blink_detected = True
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contours = []
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cursor_alpha = max(cursor_alpha - cursor_step, 0.0)
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cursor_alpha = min(cursor_alpha + cursor_step, 1.0)
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else:
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x_pred = y_pred = None
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blink_detected = True
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contours = []
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cursor_alpha = max(cursor_alpha - cursor_step, 0.0)
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canvas = background.copy()
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canvas = background.copy()
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if filter_method == "kde" and contours:
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cv2.drawContours(canvas, contours, -1, (15, 182, 242), 5)
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if filter_method == "kde" and contours:
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cv2.drawContours(canvas, contours, -1, (15, 182, 242), 5)
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if x_pred is not None and y_pred is not None and cursor_alpha > 0:
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overlay = canvas.copy()
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cv2.circle(overlay, (x_pred, y_pred), 30, (0, 0, 255), -1)
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cv2.circle(overlay, (x_pred, y_pred), 25, (255, 255, 255), -1)
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cv2.addWeighted(
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overlay,
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cursor_alpha * 0.6,
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canvas,
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1 - cursor_alpha * 0.6,
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0,
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canvas,
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)
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if x_pred is not None and y_pred is not None and cursor_alpha > 0:
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overlay = canvas.copy()
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cv2.circle(overlay, (x_pred, y_pred), 30, (0, 0, 255), -1)
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cv2.circle(overlay, (x_pred, y_pred), 25, (255, 255, 255), -1)
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cv2.addWeighted(
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overlay, cursor_alpha * 0.6, canvas, 1 - cursor_alpha * 0.6, 0, canvas
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small = cv2.resize(frame, (cam_width, cam_height))
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thumb = cv2.copyMakeBorder(
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small,
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BORDER,
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BORDER,
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BORDER,
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BORDER,
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cv2.BORDER_CONSTANT,
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value=(255, 255, 255),
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)
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h, w = thumb.shape[:2]
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canvas[-h - MARGIN : -MARGIN, -w - MARGIN : -MARGIN] = thumb
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now = time.time()
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fps = 1 / (now - prev_time)
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prev_time = now
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cv2.putText(
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canvas,
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f"FPS: {int(fps)}",
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(50, 50),
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cv2.FONT_HERSHEY_SIMPLEX,
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1.2,
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(255, 255, 255),
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2,
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cv2.LINE_AA,
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)
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blink_txt = "Blinking" if blink_detected else "Not Blinking"
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blink_clr = (0, 0, 255) if blink_detected else (0, 255, 0)
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cv2.putText(
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canvas,
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blink_txt,
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(50, 100),
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cv2.FONT_HERSHEY_SIMPLEX,
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1.2,
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blink_clr,
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2,
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cv2.LINE_AA,
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)
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small = cv2.resize(frame, (cam_width, cam_height))
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thumb = cv2.copyMakeBorder(
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small,
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BORDER,
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BORDER,
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BORDER,
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BORDER,
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cv2.BORDER_CONSTANT,
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value=(255, 255, 255),
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)
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h, w = thumb.shape[:2]
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canvas[-h - MARGIN : -MARGIN, -w - MARGIN : -MARGIN] = thumb
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now = time.time()
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fps = 1 / (now - prev_time)
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prev_time = now
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cv2.putText(
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canvas,
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f"FPS: {int(fps)}",
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(50, 50),
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cv2.FONT_HERSHEY_SIMPLEX,
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1.2,
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(255, 255, 255),
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2,
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cv2.LINE_AA,
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)
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blink_txt = "Blinking" if blink_detected else "Not Blinking"
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blink_clr = (0, 0, 255) if blink_detected else (0, 255, 0)
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cv2.putText(
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canvas,
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blink_txt,
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(50, 100),
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cv2.FONT_HERSHEY_SIMPLEX,
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1.2,
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blink_clr,
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2,
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cv2.LINE_AA,
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)
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cv2.imshow("Gaze Estimation", canvas)
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if cv2.waitKey(1) == 27:
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break
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cap.release()
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cv2.destroyAllWindows()
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cv2.imshow("Gaze Estimation", canvas)
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if cv2.waitKey(1) == 27:
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break
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if __name__ == "__main__":
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@@ -1,9 +1,9 @@
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import argparse
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import time
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import cv2
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import numpy as np
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import pyvirtualcam
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from eyetrax.utils.screen import get_screen_size
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from eyetrax.utils.video import camera, iter_frames
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from eyetrax.gaze import GazeEstimator
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from eyetrax.calibration import (
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run_9_point_calibration,
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@@ -51,53 +51,38 @@ def run_virtualcam():
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kalman = None
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smoother = NoSmoother()
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cap = cv2.VideoCapture(camera_index)
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if not cap.isOpened():
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print("Error: cannot open camera.")
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return
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cam_fps = int(cap.get(cv2.CAP_PROP_FPS)) or 30
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green_bg = np.zeros((screen_height, screen_width, 3), dtype=np.uint8)
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green_bg[:] = (0, 255, 0)
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with pyvirtualcam.Camera(
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width=screen_width,
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height=screen_height,
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fps=cam_fps,
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fmt=pyvirtualcam.PixelFormat.BGR,
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) as cam:
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print(f"Virtual camera started: {cam.device}")
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with camera(camera_index) as cap:
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cam_fps = int(cap.get(cv2.CAP_PROP_FPS)) or 30
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with pyvirtualcam.Camera(
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width=screen_width,
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height=screen_height,
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fps=cam_fps,
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fmt=pyvirtualcam.PixelFormat.BGR,
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) as cam:
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print(f"Virtual camera started: {cam.device}")
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for frame in iter_frames(cap):
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features, blink_detected = gaze_estimator.extract_features(frame)
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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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continue
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if features is not None and not blink_detected:
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gaze_point = gaze_estimator.predict(np.array([features]))[0]
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x, y = map(int, gaze_point)
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x_pred, y_pred = smoother.step(x, y)
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contours = smoother.debug.get("contours", [])
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else:
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x_pred = y_pred = None
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contours = []
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features, blink_detected = gaze_estimator.extract_features(frame)
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output = green_bg.copy()
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if contours:
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cv2.drawContours(output, contours, -1, (0, 0, 255), 3)
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if x_pred is not None and y_pred is not None:
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cv2.circle(output, (x_pred, y_pred), 10, (0, 0, 255), -1)
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if features is not None and not blink_detected:
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gaze_point = gaze_estimator.predict(np.array([features]))[0]
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x, y = map(int, gaze_point)
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x_pred, y_pred = smoother.step(x, y)
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contours = smoother.debug.get("contours", [])
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else:
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x_pred = y_pred = None
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contours = []
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output = green_bg.copy()
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if contours:
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cv2.drawContours(output, contours, -1, (0, 0, 255), 3)
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if x_pred is not None and y_pred is not None:
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cv2.circle(output, (x_pred, y_pred), 10, (0, 0, 255), -1)
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cam.send(output)
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cam.sleep_until_next_frame()
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cap.release()
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cv2.destroyAllWindows()
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cam.send(output)
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cam.sleep_until_next_frame()
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if __name__ == "__main__":
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35
src/eyetrax/utils/video.py
Normal file
35
src/eyetrax/utils/video.py
Normal file
@@ -0,0 +1,35 @@
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from __future__ import annotations
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from contextlib import contextmanager
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import cv2
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@contextmanager
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def fullscreen(name: str):
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"""Open a window in full-screen mode"""
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cv2.namedWindow(name, cv2.WND_PROP_FULLSCREEN)
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cv2.setWindowProperty(name, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
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try:
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yield
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finally:
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cv2.destroyWindow(name)
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@contextmanager
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def camera(index: int = 0):
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"""Context manager returning an opened VideoCapture"""
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cap = cv2.VideoCapture(index)
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if not cap.isOpened():
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raise RuntimeError(f"cannot open camera {index}")
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try:
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yield cap
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finally:
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cap.release()
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def iter_frames(cap: cv2.VideoCapture):
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"""Infinite generator yielding successive frames"""
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while True:
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ok, frame = cap.read()
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if not ok:
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continue
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yield frame
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