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Merge branch 'model-on-test' of github.com:albfan/howdy into albfan-model-on-test

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boltgolt 2023-02-18 21:17:56 +01:00
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1 changed files with 40 additions and 3 deletions
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43
howdy/src/cli/test.py
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@ -2,11 +2,14 @@
# Import required modules # Import required modules
import configparser import configparser
import builtins
import os import os
import json
import sys import sys
import time import time
import dlib import dlib
import cv2 import cv2
import numpy as np
from recorders.video_capture import VideoCapture from recorders.video_capture import VideoCapture
from i18n import _ from i18n import _
@ -60,6 +63,22 @@ if use_cnn:
else: else:
face_detector = dlib.get_frontal_face_detector() face_detector = dlib.get_frontal_face_detector()
pose_predictor = dlib.shape_predictor(path + "/../dlib-data/shape_predictor_5_face_landmarks.dat")
face_encoder = dlib.face_recognition_model_v1(path + "/../dlib-data/dlib_face_recognition_resnet_model_v1.dat")
encodings = []
models = None
try:
user = builtins.howdy_user
models = json.load(open(path + "/../models/" + user + ".dat"))
for model in models:
encodings += model["data"]
except FileNotFoundError:
print("No face model known for the user " + user + ", please run:")
print("\n\tsudo howdy -U " + user + " add\n")
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8)) clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
# Open the window and attach a a mouse listener # Open the window and attach a a mouse listener
@ -81,7 +100,7 @@ rec_tm = 0
# Wrap everything in an keyboard interupt handler # Wrap everything in an keyboard interupt handler
try: try:
while True: while cv2.getWindowProperty("Howdy Test", cv2.WND_PROP_VISIBLE) > 0:
frame_tm = time.time() frame_tm = time.time()
# Increment the frames # Increment the frames
@ -98,7 +117,8 @@ try:
sec_frames = 0 sec_frames = 0
# Grab a single frame of video # Grab a single frame of video
ret, frame = video_capture.read_frame() orig_frame, frame = video_capture.read_frame()
frame = clahe.apply(frame) frame = clahe.apply(frame)
# Make a frame to put overlays in # Make a frame to put overlays in
@ -156,6 +176,23 @@ try:
if use_cnn: if use_cnn:
loc = loc.rect loc = loc.rect
color = (0, 0, 230)
if models:
face_landmark = pose_predictor(orig_frame, loc)
face_encoding = np.array(face_encoder.compute_face_descriptor(orig_frame, face_landmark, 1))
# Match this found face against a known face
matches = np.linalg.norm(encodings - face_encoding, axis=1)
# Get best match
match_index = np.argmin(matches)
match = matches[match_index]
percent = match * 100
label = models[match_index]["label"]
color = (230, 0, 0)
cv2.putText(overlay, "{} {}(%)".format(label, percent), (width - 68, 32), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 255, 0), 0, cv2.LINE_AA)
# Get the center X and Y from the rectangular points # Get the center X and Y from the rectangular points
x = int((loc.right() - loc.left()) / 2) + loc.left() x = int((loc.right() - loc.left()) / 2) + loc.left()
y = int((loc.bottom() - loc.top()) / 2) + loc.top() y = int((loc.bottom() - loc.top()) / 2) + loc.top()
@ -166,7 +203,7 @@ try:
r = int(r + (r * 0.2)) r = int(r + (r * 0.2))
# Draw the Circle in green # Draw the Circle in green
cv2.circle(overlay, (x, y), r, (0, 0, 230), 2) cv2.circle(overlay, (x, y), r, color, 2)
# Add the overlay to the frame with some transparency # Add the overlay to the frame with some transparency
alpha = 0.65 alpha = 0.65