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Dropped fswebcam in add command
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boltgolt
parent
7c9a8ad849
commit
038667ef09
2 changed files with 50 additions and 54 deletions
97
cli/add.py
97
cli/add.py
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@ -6,6 +6,7 @@ import time
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import os
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import sys
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import json
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import cv2
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import configparser
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# Try to import face_recognition and give a nice error if we can't
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@ -26,50 +27,8 @@ path = os.path.dirname(os.path.abspath(__file__))
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config = configparser.ConfigParser()
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config.read(path + "/../config.ini")
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def captureFrame(delay):
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"""Capture and encode 1 frame of video"""
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global insert_model
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# Call fswebcam to save a frame to /tmp with a set delay
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exit_code = subprocess.call(["fswebcam", "-S", str(delay), "--no-banner", "-d", "/dev/video" + str(config.get("video", "device_id")), tmp_file])
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# Check if fswebcam exited normally
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if (exit_code != 0):
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print("Webcam frame capture failed!")
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print("Please make sure fswebcam is installed on this system")
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sys.exit()
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# Try to load the image from disk
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try:
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ref = face_recognition.load_image_file(tmp_file)
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except FileNotFoundError:
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print("No webcam frame captured, check if /dev/video" + str(config.get("video", "device_id")) + " is the right webcam")
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sys.exit()
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# Make a face encoding from the loaded image
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enc = face_recognition.face_encodings(ref)
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# If 0 faces are detected we can't continue
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if len(enc) == 0:
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print("No face detected, aborting")
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sys.exit()
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# If more than 1 faces are detected we can't know wich one belongs to the user
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if len(enc) > 1:
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print("Multiple faces detected, aborting")
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sys.exit()
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clean_enc = []
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# Copy the values into a clean array so we can export it as JSON later on
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for point in enc[0]:
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clean_enc.append(point)
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insert_model["data"].append(clean_enc)
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# The current user
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user = sys.argv[1]
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# The name of the tmp frame file to user
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tmp_file = "/tmp/howdy_" + user + ".jpg"
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# The permanent file to store the encoded model in
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enc_file = path + "/../models/" + user + ".dat"
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# Known encodings
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@ -110,15 +69,52 @@ insert_model = {
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"data": []
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}
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print("\nPlease look straight into the camera for 5 seconds")
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# Open the camera
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video_capture = cv2.VideoCapture(int(config.get("video", "device_id")))
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video_capture.read()
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print("\nPlease look straight into the camera")
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# Give the user time to read
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time.sleep(2)
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# Capture with 3 different delays to simulate different camera exposures
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for delay in [30, 6, 0]:
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time.sleep(.3)
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captureFrame(delay)
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# Will contain found face encodings
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enc = []
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# Count the amount or read frames
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frames = 0
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# Loop through frames till we hit a timeout
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while frames < 60:
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frames += 1
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# Grab a single frame of video
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# Don't remove ret, it doesn't work without it
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ret, frame = video_capture.read()
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# Get the encodings in the frame
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enc = face_recognition.face_encodings(frame)
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# If we've found at least one, we can continue
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if len(enc) > 0:
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break
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# If 0 faces are detected we can't continue
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if len(enc) == 0:
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print("No face detected, aborting")
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sys.exit()
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# If more than 1 faces are detected we can't know wich one belongs to the user
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if len(enc) > 1:
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print("Multiple faces detected, aborting")
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sys.exit()
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clean_enc = []
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# Copy the values into a clean array so we can export it as JSON later on
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for point in enc[0]:
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clean_enc.append(point)
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insert_model["data"].append(clean_enc)
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# Insert full object into the list
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encodings.append(insert_model)
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@ -127,7 +123,6 @@ encodings.append(insert_model)
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with open(enc_file, "w") as datafile:
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json.dump(encodings, datafile)
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# Remove any left over temp files
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os.remove(tmp_file)
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print("Done.")
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# Give let the user know how it went
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print("Scan complete")
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print("\nAdded a new model to " + user)
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@ -125,10 +125,11 @@ while True:
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print("\nFrames searched: " + str(frames) + " (" + str(round(float(frames) / (timings[4] - timings[2]), 2)) + " fps)")
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print("Certainty of winning frame: " + str(round(match * 10, 3)))
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exposures = ["long", "medium", "short"]
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model_id = math.floor(float(match_index) / 3)
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# Catch older 3-encoding models
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if not match_index in models:
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match_index = 0
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print("Winning model: " + str(model_id) + " (\"" + models[model_id]["label"] + "\") using " + exposures[match_index % 3] + " exposure\n")
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print("Winning model: " + str(match_index) + " (\"" + models[match_index]["label"] + "\")")
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# End peacegully
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stop(0)
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