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a_history_of_the_domino_problem
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all plumbing in place for the motion tracker

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legacy 0.1
Michael Winter 5 years ago
parent 78b1ddeb6b
commit a80fc87a8b
4 changed files with 164 additions and 72 deletions
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18
openstagecontrol/stepper_control_gui.json
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@ -40,7 +40,7 @@
"height": 312,
"label": false,
"color": "auto",
"css": "> .panel {\n background-color: black;\n border: 2px solid grey;\n}\n:host {\n top:calc(50% - 156rem);\n left:calc(50% - 251rem);\n}",
"css": "> .panel {\n background-color: black;\n border: 2px solid grey;\n}\n:host {\n top:calc(50% - 156rem);\n left:calc(50% - 251rem);\n z-index:15;\n}",
"scroll": true,
"border": true,
"default": "",
@ -639,6 +639,22 @@
}
],
"tabs": []
},
{
"type": "frame",
"top": "auto",
"left": "auto",
"id": "frame_3",
"linkId": "",
"width": 600,
"height": 400,
"label": "auto",
"css": "> .frame {\n background-color: black;\n border: 2px solid grey;\n}\n:host {\n top:calc(50% - 200rem);\n left:calc(50% - 800rem);\n z-index: 10;\n}",
"border": true,
"default": "",
"value": "http://10.0.0.5:5000",
"address": "/frame_3",
"preArgs": ""
}
],
"tabs": [],

9
python/templates/index.html
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@ -0,0 +1,9 @@
<html>
<head>
<title>Video Streaming Demonstration</title>
</head>
<body>
<h1>Video Streaming Demonstration</h1>
<img src="{{ url_for('video_feed') }}">
</body>
</html>

201
python/vernier_tracker.py
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@ -1,12 +1,24 @@
#This is a proof of concept for motion tracking of the vernier in very early stages
# TODO: stabilize the tracker and connect the plumbing via OSC to the SuperCollider app
# and get the stream to feed to the Open Stage Control GUI for calibration
import cv2
import sys
from pythonosc.udp_client import SimpleUDPClient
from flask import Flask, render_template, Response
import threading
import argparse
outputFrame = None
lock = threading.Lock()
app = Flask(__name__)
ip = "127.0.0.1"
port = 57120
client = SimpleUDPClient(ip, port) # Create client
# Read video (eventually will be the live capture from the camera)
video = cv2.VideoCapture("/home/mwinter/Sketches/a_history_of_the_domino_problem/recs/a_history_of_the_domino_problem_final_documentation_hq.mp4")
video = cv2.VideoCapture("/home/mwinter/Portfolio/a_history_of_the_domino_problem/a_history_of_the_domino_problem/recs/a_history_of_the_domino_problem_final_documentation_hq.mp4")
# Exit if video not opened.
if not video.isOpened():
@ -15,85 +27,136 @@ if not video.isOpened():
# Read first frame.
video.set(cv2.CAP_PROP_POS_FRAMES, 5000)
ok, frame = video.read()
ok, initFrame = video.read()
if not ok:
print('Cannot read video file')
sys.exit()
# Define an initial bounding box
#bbox = (287, 23, 86, 320)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
#frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
#frame = cv2.GaussianBlur(frame,(5,5),cv2.BORDER_DEFAULT)
r1 = cv2.selectROI('Tracking', frame)
r2 = cv2.selectROI('Tracking', frame)
#r = (606, 448, 35, 177);
#cv2.destroyWindow('select')
#print(r)
crop1 = frame[int(r1[1]):int(r1[1]+r1[3]), int(r1[0]):int(r1[0]+r1[2])]
crop2 = frame[int(r2[1]):int(r2[1]+r2[3]), int(r2[0]):int(r2[0]+r2[2])]
# all this for selecting ROI
#xROI = cv2.selectROI('Tracking', initFrame)
#yROI = cv2.selectROI('Tracking', initFrame)
#print(xROI)
#print(yROI)
#xFine = (xROI[0], xROI[1], xROI[2], xROI[3] / 2)
#xCourse = (xROI[0], xROI[1] + (xROI[3] / 2), xROI[2], xROI[3] / 2)
#yFine = (yROI[0], yROI[1], yROI[2] / 2, yROI[3])
#yCourse = (yROI[0] + (yROI[2] / 2), yROI[1], yROI[2] / 2, yROI[3])
#print(xFine)
#print(yFine)
xFine = (848, 187, 225, 21.0)
yFine = (604, 402, 20.5, 276)
while True:
# Read a new frame
ok, frame = video.read()
if not ok:
break
frameCountMod = 0
centroidX = [0, 0]
centroidY = [0, 0]
def track(frame, ROI, centroid, update):
if(update):
crop = frame[int(ROI[1]):int(ROI[1]+ROI[3]), int(ROI[0]):int(ROI[0]+ROI[2])]
crop = cv2.cvtColor(crop, cv2.COLOR_RGB2GRAY)
crop = cv2.GaussianBlur(crop,(7,7),cv2.BORDER_DEFAULT)
#ret, thresh = cv2.threshold(crop, 100, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)
ret,thresh = cv2.threshold(crop, 50, 255, 0)
M = cv2.moments(thresh)
crop1 = frame[int(r1[1]):int(r1[1]+r1[3]), int(r1[0]):int(r1[0]+r1[2])]
crop1 = cv2.cvtColor(crop1, cv2.COLOR_RGB2GRAY)
crop1 = cv2.GaussianBlur(crop1,(5,5),cv2.BORDER_DEFAULT)
crop2 = frame[int(r2[1]):int(r2[1]+r2[3]), int(r2[0]):int(r2[0]+r2[2])]
crop2 = cv2.cvtColor(crop2, cv2.COLOR_RGB2GRAY)
crop2 = cv2.GaussianBlur(crop2,(5,5),cv2.BORDER_DEFAULT)
ret1, thresh1 = cv2.threshold(crop1, 230, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)
cnts1 = cv2.findContours(thresh1.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts1 = cnts1[1]
ret2, thresh2 = cv2.threshold(crop2, 230, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)
cnts2 = cv2.findContours(thresh2.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts2 = cnts2[1]
center = None
for c in cnts1[0:2]:
# calculate moments for each contour
M = cv2.moments(c)
# calculate x,y coordinate of center
if M["m00"] != 0:
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
centroid[0] = int(M["m10"] / M["m00"])
centroid[1] = int(M["m01"] / M["m00"])
#else:
# cX, cY = 0, 0
#print(cY)
cv2.circle(frame, (int(r1[0]) + cX, int(r1[1]) + cY), 5, (255, 255, 255), -1)
cv2.circle(frame, (int(ROI[0]) + centroid[0], int(ROI[1]) + centroid[1]), 5, (255, 255, 255), -1)
def detect_motion():
# grab global references to the video stream, output frame, and
# lock variables
global vs, outputFrame, lock
frameCountMod = 0
centroidX = [0, 0]
centroidY = [0, 0]
"""Video streaming generator function."""
while True:
# Read a new frame
ok, frame = video.read()
if not ok:
break
if(frameCountMod == 0):
track(frame, xFine, centroidX, True)
track(frame, yFine, centroidY, True)
xPos = (centroidX[0] / xFine[2]) * 2 - 1
yPos = (centroidY[1] / yFine[3]) * 2 - 1
client.send_message("/trackerpos", [xPos, yPos])
else:
track(frame, xFine, centroidX, False)
track(frame, yFine, centroidY, False)
frameCountMod = (frameCountMod + 1) % 10
cv2.rectangle(frame, (int(xFine[0]), int(xFine[1])), (int(xFine[0]+int(xFine[2])),int(xFine[1]+xFine[3])), (255, 255, 255), 5)
cv2.rectangle(frame, (int(yFine[0]), int(yFine[1])), (int(yFine[0]+int(yFine[2])),int(yFine[1]+yFine[3])), (255, 255, 255), 5)
# Display result
#cv2.imshow("Tracking", frame)
#cv2.imshow("Crop", crop)
# only proceed if at least one contour was found
if len(cnts2) > 0:
# find the largest contour in the mask, then use
# it to compute the minimum enclosing circle and
# centroid
c = max(cnts2, key=cv2.contourArea)
((x, y), radius) = cv2.minEnclosingCircle(c)
M = cv2.moments(c)
center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
# only proceed if the radius meets a minimum size
if radius > 5:
# draw the circle and centroid on the frame,
# then update the list of tracked points
cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
cv2.circle(frame, center, 5, (0, 0, 255), -1)
with lock:
outputFrame = frame.copy()
# Exit if ESC pressed
#k = cv2.waitKey(1) & 0xff
#if k == 27 :
# cv2.destroyWindow('Tracking')
# break
# Display result
cv2.imshow("Tracking", frame)
#cv2.imshow("Crop", crop)
# Exit if ESC pressed
k = cv2.waitKey(1) & 0xff
if k == 27 :
cv2.destroyWindow('Tracking')
break
@app.route('/')
def index():
"""Video streaming home page."""
return render_template('index.html')
def generate():
# grab global references to the output frame and lock variables
global outputFrame, lock
# loop over frames from the output stream
while True:
# wait until the lock is acquired
with lock:
# check if the output frame is available, otherwise skip
# the iteration of the loop
if outputFrame is None:
continue
# encode the frame in JPEG format
(flag, encodedImage) = cv2.imencode(".jpg", outputFrame)
# ensure the frame was successfully encoded
if not flag:
continue
# yield the output frame in the byte format
yield(b'--frame\r\n' b'Content-Type: image/jpeg\r\n\r\n' +
bytearray(encodedImage) + b'\r\n')
@app.route('/video_feed')
def video_feed():
"""Video streaming route. Put this in the src attribute of an img tag."""
return Response(generate(),mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
t = threading.Thread(target=detect_motion)
t.daemon = True
t.start()
app.run(host='10.0.0.5', threaded=True)

8
supercollider/installation_control.scd
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@ -4,7 +4,7 @@
var imageDist, micronsPerStep, automation, imgPositions, curPos, tarPos,
netAddress, serialPort, serialListener,
moveTo, jogControl, jogHorizontal, jogVertical,
imgSelect, imgCalibrate, automate, lastSelect;
imgSelect, imgCalibrate, automate, lastSelect, trackerPos;
// init global vars
imageDist = 300; // in microns
@ -27,7 +27,7 @@ netAddress = NetAddr.new("127.0.0.1", 7777);
byte = ~serialPort.read;
if(byte==13, {
if(str[1].asString == "[", {
valArray = str.asString.interpret.postln;
valArray = str.asString.interpret; //.postln;
curPos = Point.new(valArray[0], valArray[1]);
limitSwitchNeg = valArray[2];
limitSwitchPos = valArray[3];
@ -152,6 +152,10 @@ automate = OSCFunc({arg msg;
});
9.do({arg i; netAddress.sendMsg("/STATE/SET", "{img_" ++ (i + 1).asString ++ "_select: " ++ (i + 1).neg ++ "}")});
}, '/automate', netAddress);
trackerPos = OSCFunc({arg msg;
msg.postln;
}, '/trackerpos');
)
~serialPort.close
~serialPort = SerialPort.new("/dev/ttyACM0", baudrate: 115200, crtscts: true);

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