I am running the meanshift tracking algorithm to track objects in a live stream(with webcam) in OpenCV however the algorithm only works the first time it is run and does not work when I run the program again unless I restart my computer. Why is this so?
Algorithm taken from: https://docs.opencv.org/trunk/db/df8/tutorial_py_meanshift.html
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
# take first frame of the video
ret,frame = cap.read()
# setup initial location of window
r,h,c,w = 250,90,400,125 # simply hardcoded the values
track_window = (c,r,w,h)
# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)
# Setup the termination criteria, either 10 iteration or move by atleast 1 pt
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
while(1):
ret ,frame = cap.read()
if ret == True:
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv],[0],roi_hist,[0,180],1)
# apply meanshift to get the new location
ret, track_window = cv2.meanShift(dst, track_window, term_crit)
# Draw it on image
x,y,w,h = track_window
img2 = cv2.rectangle(frame, (x,y), (x+w,y+h), 255,2)
cv2.imshow('img2',img2)
k = cv2.waitKey(60) & 0xff
if k == 27:
break
else:
cv2.imwrite(chr(k)+".jpg",img2)
else:
break
cv2.destroyAllWindows()
cap.release()
Related
i am trying to make a code about a drone flying to multiple waypoint and the drone can't continue to the next waypoint when i not showing the red color on camera.
because the camera cv2 and the drone runs at the same time, my code runs very laggy, so i tried using multiprocessing method and modify my code. when i trying to run my new code, my multi processing doesn't work and it keeps skipping almost of my code and straight to RTL mode.
from inspect import ArgInfo
from dronekit import connect, VehicleMode, LocationGlobalRelative
from pymavlink import mavutil
from numpy import loadtxt, array
from time import sleep
import sys
import cv2
import numpy as np
import multiprocessing
cap = cv2.VideoCapture(0)
hsv_a = np.array([198, 255, 255])
hsv_b = np.array([158, 68, 137])
treshold = 150
lat = [-35.3629722, -35.3629064, -35.3634361, -35.3638474]
lon = [149.1649709, 149.1655721, 149.1657331, 149.1639733]
#vehicle = connect('udp:127.0.0.1:14551',wait_ready=True)
vehicle = connect('udp:127.0.0.1:14551',wait_ready=True)
def arm_and_takeoff(aTargetAltitude): #fungsi arming dan takeoff
print("Basic pre-arm checks")
# Don't let the user try to arm until autopilot is ready
while not(vehicle.is_armable):
print(" Waiting for vehicle to initialise...")
sleep(1)
print("Arming motors")
# Copter should arm in GUIDED mode
vehicle.mode = VehicleMode("GUIDED")
vehicle.armed = True
while not(vehicle.armed):
print(" Waiting for arming...")
sleep(1)
print("Taking off!")
vehicle.simple_takeoff(aTargetAltitude)
while True:
print(" Altitude: ", vehicle.location.global_relative_frame.alt)
#Break and return from function just below target altitude.
if (vehicle.location.global_relative_frame.alt>=aTargetAltitude*0.95):
print("Reached target altitude")
break
sleep(1)
def dist(a,z): #a=awal z=akhir
d_lat= (a.lat-z.lat)**2
d_long= (a.lon-z.lon)**2
jarak = (d_lat+d_long)**0.5
return jarak
def gerak_drone():
for i in range(0,len(lat)):
print(i)
wp = LocationGlobalRelative(lat[i],lon[i],2)
vehicle.simple_goto(wp)
sleep(1)
while (dist(vehicle.location.global_relative_frame,wp)>=0.0001):
print (str(round(dist(vehicle.location.global_relative_frame,wp)*100000,2)))
while True:
_,frame = cap.read()
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
mask = cv2.inRange(hsv, hsv_b, hsv_a)
cv2.imshow("warna", mask)
cv2.imshow("hitamPutih", gray)
cv2.imshow("apa", frame)
print(cv2.countNonZero(mask))
if cv2.waitKey(500) == 27 or cv2.countNonZero(mask) > treshold :
break
if __name__ == "_main_":
altitude = 2
lat_distance = 1
lon_distance = 1
p1 = multiprocessing.Process(target=arm_and_takeoff, args=(altitude))
p2 = multiprocessing.Process(target=dist, args=(lat_distance, lon_distance))
p3 = multiprocessing.Process(target=gerak_drone)
p1.start()
p2.start()
p3.start()
p1.join()
p2.join()
p3.join()
print("Coming back")
vehicle.mode = VehicleMode("RTL")
sleep(20)
vehicle.mode = VehicleMode("LAND")
Here is my terminal result
I need some help with this code.....,
the error is "TypeError: 'NormalizedLandmarkList' object is not iterable mediapipe".
In the 19th line of the code.
import cv2
import mediapipe as mp
import math
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.holistic
hands = mp_hands.Holistic(static_image_mode=True, )
cap = cv2.VideoCapture(0)
while True:
_, frame = cap.read()
frame = cv2.flip(frame, 1)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
results = hands.process(frame)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
if results.left_hand_landmarks:
for hand_landmarks in results.left_hand_landmarks:
mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
keypoint_pos = []
for i in range(21):
x = hand_landmarks.landmark[i].x * frame.shape[1]
y = hand_landmarks.landmark[i].y * frame.shape[0]
keypoint_pos.append((x, y))
cv2.imshow('MediaPipe Hands', frame)
if cv2.waitKey(1) & 0xFF == 27:
break
cap.release()
To access the iterable hand landmarks, we need to do the following.
for hand_landmarks in results.left_hand_landmarks.landmark
Also, make sure to set static_image_mode to False for videos as it has related frames. You can check out this GitHub issue as well.
I'm trying to count the number of piglets that enter and leave a zone. This is important because, in my project, there is a balance underneath the zone that computes the weight of the animals. My goal is to find the pig's weight, so, to achieve that, I will count the number of piglets that enter the zone, and if this number is zero, I have the pig's weight, and according to the number of piglets that get in I will calculate the weight of each as well.
But the weight history is for the future. Currently, I need help in the counting process.
The video can be seen here. The entrance occurs from the minute 00:40 until 02:00 and the exit starts on the minute 03:54 and goes all the way through the video because the piglets start, at this point, to enter and exit the zone.
I've successfully counted the entrance with the code below. I defined a region of interest, very small, and filter the pigs according to their colors. It works fine until the piglets start to move around and get very active, leaving and entering the zone all the time.
I'm out of ideas to proceed with this challenge. If you have any suggestions, please, tell me!
Thanks!!
import cv2
FULL_VIDEO_PATH = "PATH TO THE FULL VIDEO"
MAX_COLOR = (225, 215, 219)
MIN_COLOR = (158, 141, 148)
def get_centroid(x, y, w, h):
x1 = int(w / 2)
y1 = int(h / 2)
cx = x + x1
cy = y + y1
return cx, cy
def filter_mask(frame):
# create a copy from the ROI to be filtered
ROI = (frame[80:310, 615:620]).copy()
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
# create a green rectangle on the structure that creates noise
thicker_line_filtered = cv2.rectangle(ROI, (400, 135), (0, 165), (20, 200, 20), -1)
closing = cv2.morphologyEx(thicker_line_filtered, cv2.MORPH_CLOSE, kernel)
opening = cv2.morphologyEx(closing, cv2.MORPH_OPEN, kernel)
dilation = cv2.dilate(opening, kernel, iterations=2)
# Filter the image according to the colors
segmented_line = cv2.inRange(dilation, MIN_COLOR, MAX_COLOR)
# Resize segmented line only for plot
copy = cv2.resize(segmented_line, (200, 400))
cv2.imshow('ROI', copy)
return segmented_line
def count_pigs():
cap = cv2.VideoCapture(FULL_VIDEO_PATH)
ret, frame = cap.read()
total_pigs = 0
frames_not_seen = 0
last_center = 0
is_position_ok = False
is_size_ok = False
total_size = 0
already_counted = False
while ret:
# Window interval used for counting
count_window_interval = (615, 0, 620, 400)
# Filter frame
fg_mask = filter_mask(frame)
# Draw a line on the frame, which represents when the pigs will be counted
frame_with_line = cv2.line(frame, count_window_interval[0:2], count_window_interval[2:4],(0,0,255), 1)
contours, _ = cv2.findContours(fg_mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# If no contour is found, increments the variable
if len(contours) == 0:
frames_not_seen += 1
# If no contours are found within 5 frames, set last_center to 0 to generate the position difference when
# a new counter is found.
if frames_not_seen > 5:
last_center = 0
for c in contours:
frames_not_seen = 0
# Find the contour coordinates
(x, y, w, h) = cv2.boundingRect(c)
# Calculate the rectangle's center
centroid = get_centroid(x, y, w, h)
# Get the moments from the contour to calculate its size
moments = cv2.moments(c)
# Get contour's size
size = moments['m00']
# Sum the size until count the current pig
if not already_counted:
total_size += size
# If the difference between the last center and the current one is bigger than 80 - which means a new pig
# enter the counting zone - set the position ok and set the already_counted to False to mitigate noises
# with significant differences to be counted
if abs(last_center - centroid[1]) > 80:
is_position_ok = True
already_counted = False
# Imposes limits to the size to evaluate if the contour is consistent
# Min and Max value determined experimentally
if 1300 < total_size < 5500:
is_size_ok = True
# If all conditions are True, count the pig and reset all of them.
if is_position_ok and is_size_ok and not already_counted:
is_position_ok = False
is_size_ok = False
already_counted = True
total_size = 0
total_pigs += 1
last_center = centroid[1]
frame_with_line = cv2.putText(frame_with_line, f'Pigs: {total_pigs}', (100, 370) , cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0,0,0), 2)
cv2.imshow('Frame', frame_with_line)
cv2.moveWindow('ROI', 1130, 0)
cv2.moveWindow('Frame', 0, 0)
k = cv2.waitKey(15) & 0xff
if k == 27:
break
elif k == 32:
cv2.waitKey() & 0xff
ret, frame = cap.read()
cv2.destroyAllWindows()
cap.release()
if __name__ == '__main__':
count_pigs()
To start with, I am not a developer, but a mere automation engineer that have worked a bit with coding in Java, python, C#, C++ and C.
I am trying to make a prototype that take pictures and stores them using a digital pin on the board. Atm I can take pictures using a switch, but it is really slow(around 3 seconds pr image).
My complete system is going to be like this:
A product passes by on a conveyor and a photo cell triggers the board to take an image and store it. If an operator removes a product(because of bad quality) the image is stored in a different folder.
I started with the snapshot function shipped with Mendel and have tried to get rid off the overhead, but the Gstream and pipeline-stuff confuses me a lot.
If someone could help me with how to understand the supplied code, or how to write a minimalistic solution to take an image i would be grateful :)
I have tried to understand and use project-teachable and examples-camera from Google coral https://github.com/google-coral, but with no luck. I have had the best luck with the snapshot tool that uses snapshot.py that are referenced here https://coral.withgoogle.com/docs/camera/datasheet/#snapshot-tool
from periphery import GPIO
import time
import argparse
import contextlib
import fcntl
import os
import select
import sys
import termios
import threading
import gi
gi.require_version('Gst', '1.0')
gi.require_version('GstBase', '1.0')
from functools import partial
from gi.repository import GLib, GObject, Gst, GstBase
from PIL import Image
GObject.threads_init()
Gst.init(None)
WIDTH = 2592
HEIGHT = 1944
FILENAME_PREFIX = 'img'
FILENAME_SUFFIX = '.png'
AF_SYSFS_NODE = '/sys/module/ov5645_camera_mipi_v2/parameters/ov5645_af'
CAMERA_INIT_QUERY_SYSFS_NODE = '/sys/module/ov5645_camera_mipi_v2/parameters/ov5645_initialized'
HDMI_SYSFS_NODE = '/sys/class/drm/card0/card0-HDMI-A-1/status'
# No of initial frames to throw away before camera has stabilized
SCRAP_FRAMES = 1
SRC_WIDTH = 2592
SRC_HEIGHT = 1944
SRC_RATE = '15/1'
SRC_ELEMENT = 'v4l2src'
SINK_WIDTH = 2592
SINK_HEIGHT = 1944
SINK_ELEMENT = ('appsink name=appsink sync=false emit-signals=true '
'max-buffers=1 drop=true')
SCREEN_SINK = 'glimagesink sync=false'
FAKE_SINK = 'fakesink sync=false'
SRC_CAPS = 'video/x-raw,format=YUY2,width={width},height={height},framerate={rate}'
SINK_CAPS = 'video/x-raw,format=RGB,width={width},height={height}'
LEAKY_Q = 'queue max-size-buffers=1 leaky=downstream'
PIPELINE = '''
{src_element} ! {src_caps} ! {leaky_q} ! tee name=t
t. ! {leaky_q} ! {screen_sink}
t. ! {leaky_q} ! videoconvert ! {sink_caps} ! {sink_element}
'''
def on_bus_message(bus, message, loop):
t = message.type
if t == Gst.MessageType.EOS:
loop.quit()
elif t == Gst.MessageType.WARNING:
err, debug = message.parse_warning()
sys.stderr.write('Warning: %s: %s\n' % (err, debug))
elif t == Gst.MessageType.ERROR:
err, debug = message.parse_error()
sys.stderr.write('Error: %s: %s\n' % (err, debug))
loop.quit()
return True
def on_new_sample(sink, snapinfo):
if not snapinfo.save_frame():
# Throw away the frame
return Gst.FlowReturn.OK
sample = sink.emit('pull-sample')
buf = sample.get_buffer()
result, mapinfo = buf.map(Gst.MapFlags.READ)
if result:
imgfile = snapinfo.get_filename()
caps = sample.get_caps()
width = WIDTH
height = HEIGHT
img = Image.frombytes('RGB', (width, height), mapinfo.data, 'raw')
img.save(imgfile)
img.close()
buf.unmap(mapinfo)
return Gst.FlowReturn.OK
def run_pipeline(snapinfo):
src_caps = SRC_CAPS.format(width=SRC_WIDTH, height=SRC_HEIGHT, rate=SRC_RATE)
sink_caps = SINK_CAPS.format(width=SINK_WIDTH, height=SINK_HEIGHT)
screen_sink = FAKE_SINK
pipeline = PIPELINE.format(
leaky_q=LEAKY_Q,
src_element=SRC_ELEMENT,
src_caps=src_caps,
sink_caps=sink_caps,
sink_element=SINK_ELEMENT,
screen_sink=screen_sink)
pipeline = Gst.parse_launch(pipeline)
appsink = pipeline.get_by_name('appsink')
appsink.connect('new-sample', partial(on_new_sample, snapinfo=snapinfo))
loop = GObject.MainLoop()
# Set up a pipeline bus watch to catch errors.
bus = pipeline.get_bus()
bus.add_signal_watch()
bus.connect('message', on_bus_message, loop)
# Connect the loop to the snaphelper
snapinfo.connect_loop(loop)
# Run pipeline.
pipeline.set_state(Gst.State.PLAYING)
try:
loop.run()
except:
pass
# Clean up.
pipeline.set_state(Gst.State.NULL)
while GLib.MainContext.default().iteration(False):
pass
class SnapHelper:
def __init__(self, sysfs, prefix='img', oneshot=True, suffix='jpg'):
self.prefix = prefix
self.oneshot = oneshot
self.suffix = suffix
self.snap_it = oneshot
self.num = 0
self.scrapframes = SCRAP_FRAMES
self.sysfs = sysfs
def get_filename(self):
while True:
filename = self.prefix + str(self.num).zfill(4) + '.' + self.suffix
self.num = self.num + 1
if not os.path.exists(filename):
break
return filename
#def check_af(self):
#try:
# self.sysfs.seek(0)
# v = self.sysfs.read()
# if int(v) != 0x10:
# print('NO Focus')
#except:
# pass
# def refocus(self):
# try:#
# self.sysfs.write('1')
# self.sysfs.flush()
# except:
# pass
def save_frame(self):
# We always want to throw away the initial frames to let the
# camera stabilize. This seemed empirically to be the right number
# when running on desktop.
if self.scrapframes > 0:
self.scrapframes = self.scrapframes - 1
return False
if self.snap_it:
self.snap_it = False
retval = True
else:
retval = False
if self.oneshot:
self.loop.quit()
return retval
def connect_loop(self, loop):
self.loop = loop
def take_picture(snap):
start_time = int(round(time.time()))
run_pipeline(snap)
print(time.time()- start_time)
def main():
button = GPIO(138, "in")
last_state = False
with open(AF_SYSFS_NODE, 'w+') as sysfs:
snap = SnapHelper(sysfs, 'test', 'oneshot', 'jpg')
sysfs.write('2')
while 1:
button_state = button.read()
if(button_state==True and last_state == False):
snap = SnapHelper(sysfs, 'test', 'oneshot', 'jpg')
take_picture(snap)
last_state = button_state
if __name__== "__main__":
main()
sys.exit()
Output is what i expect, but it is slow.
I switched to a USB-webcam and used the pygame library instead.
In my other question, some of the posters asked to see the code and suggested I make a new question. As requested, here is most of the code I'm using. I've removed the Vector class, simply because it's a lot of code. It's well-understood math that I got from someone else (https://gist.github.com/mcleonard/5351452), and cProfile didn't have much to say about any of the functions there. I've provided a link in the code, if you want to make this run-able.
This code should run, if you paste the the vector class where indicated in the code.
The problem is, once I get above 20 critters, the framerate drops rapidly from 60fps to 11fps around 50 critters.
Please excuse the spaghetti-code. Much of this is diagnostic kludging or pre-code that I intend to either remove, or turn into a behavior (instead of a hard-coded value).
This app is basically composed of 4 objects.
A Vector object provides abstracted vector operations.
A Heat Block is able to track it's own "heat" level, increase it and decrease it. It can also draw itself.
A Heat Map is composed of heat blocks which are tiled across the screen. When given coordinates, it can choose the block that those coordinates fall within.
A Critter has many features that make it able to wander around the screen, bump off of the walls and other critters, choose a new random direction, and die.
The main loop iterates through each critter in the "flock" and updates its "condition" (whether or not it's "dying"), its location, its orientation, and the heat block on which it is currently standing. The loop also iterates over each heat block to let it "cool down."
Then the main loop asks the heat map to draw itself, and then each critter in the flock to draw itself.
import pygame
from pygame import gfxdraw
import pygame.locals
import os
import math
import random
import time
(I got a nice vector class from someone else. It's large, and mostly likely not the problem.)
(INSERT CONTENTS OF VECTOR.PY FROM https://gist.github.com/mcleonard/5351452 HERE)
pygame.init()
#some global constants
BLUE = (0, 0, 255)
WHITE = (255,255,255)
diagnostic = False
SPAWN_TIME = 1 #number of seconds between creating new critters
FLOCK_LIMIT = 30 #number of critters at which the flock begins being culled
GUIDs = [0] #list of guaranteed unique IDs for identifying each critter
# Set the position of the OS window
position = (30, 30)
os.environ['SDL_VIDEO_WINDOW_POS'] = str(position[0]) + "," + str(position[1])
# Set the position, width and height of the screen [width, height]
size_x = 1000
size_y = 500
size = (size_x, size_y)
FRAMERATE = 60
SECS_FOR_DYING = 1
screen = pygame.display.set_mode(size)
screen.set_alpha(None)
pygame.display.set_caption("My Game")
# Used to manage how fast the screen updates
clock = pygame.time.Clock()
def random_float(lower, upper):
num = random.randint(lower*1000, upper*1000)
return num/1000
def new_GUID():
num = GUIDs[-1]
num = num + 1
while num in GUIDs:
num += 1
GUIDs.append(num)
return num
class HeatBlock:
def __init__(self,_tlx,_tly,h,w):
self.tlx = int(_tlx)
self.tly = int(_tly)
self.height = int(h)+1
self.width = int(w)
self.heat = 255.0
self.registered = False
def register_tresspasser(self):
self.registered = True
self.heat = max(self.heat - 1, 0)
def cool_down(self):
if not self.registered:
self.heat = min(self.heat + 0.1, 255)
self.registered = False
def hb_draw_self(self):
screen.fill((255,int(self.heat),int(self.heat)), [self.tlx, self.tly, self.width, self.height])
class HeatMap:
def __init__(self, _h, _v):
self.h_freq = _h #horizontal frequency
self.h_rez = size_x/self.h_freq #horizontal resolution
self.v_freq = _v #vertical frequency
self.v_rez = size_y/self.v_freq #vertical resolution
self.blocks = []
def make_map(self):
h_size = size_x/self.h_freq
v_size = size_y/self.v_freq
for h_count in range(0, self.h_freq):
TLx = h_count * h_size #TopLeft corner, x
col = []
for v_count in range(0, self.v_freq):
TLy = v_count * v_size #TopLeft corner, y
col.append(HeatBlock(TLx,TLy,v_size,h_size))
self.blocks.append(col)
def hm_draw_self(self):
for col in self.blocks:
for block in col:
block.cool_down()
block.hb_draw_self()
def register(self, x, y):
#convert the given coordinates of the trespasser into a col/row block index
col = max(int(math.floor(x / self.h_rez)),0)
row = max(int(math.floor(y / self.v_rez)),0)
self.blocks[col][row].register_tresspasser()
class Critter:
def __init__(self):
self.color = (random.randint(1, 200), random.randint(1, 200), random.randint(1, 200))
self.linear_speed = random_float(20, 100)
self.radius = int(round(10 * (100/self.linear_speed)))
self.angular_speed = random_float(0.1, 2)
self.x = int(random.randint(self.radius*2, size_x - (self.radius*2)))
self.y = int(random.randint(self.radius*2, size_y - (self.radius*2)))
self.orientation = Vector(0, 1).rotate(random.randint(-180, 180))
self.sensor = Vector(0, 20)
self.sensor_length = 20
self.new_orientation = self.orientation
self.draw_bounds = False
self.GUID = new_GUID()
self.condition = 0 #0 = alive, [1-fps] = dying, >fps = dead
self.delete_me = False
def c_draw_self(self):
#if we're alive and not dying, draw our normal self
if self.condition == 0:
#diagnostic
if self.draw_bounds:
pygame.gfxdraw.rectangle(screen, [int(self.x), int(self.y), 1, 1], BLUE)
temp = self.orientation * (self.linear_speed * 20)
pygame.gfxdraw.line(screen, int(self.x), int(self.y), int(self.x + temp[0]), int(self.y + temp[1]), BLUE)
#if there's a new orientation, match it gradually
temp = self.new_orientation * self.linear_speed
#draw my body
pygame.gfxdraw.aacircle(screen, int(self.x), int(self.y), self.radius, self.color)
#draw a line indicating my new direction
pygame.gfxdraw.line(screen, int(self.x), int(self.y), int(self.x + temp[0]), int(self.y + temp[1]), BLUE)
#draw my sensor (a line pointing forward)
self.sensor = self.orientation.normalize() * self.sensor_length
pygame.gfxdraw.line(screen, int(self.x), int(self.y), int(self.x + self.sensor[0]), int(self.y + self.sensor[1]), BLUE)
#otherwise we're dying, draw our dying animation
elif 1 <= self.condition <= FRAMERATE*SECS_FOR_DYING:
#draw some lines in a spinningi circle
for num in range(0,10):
line = Vector(0, 1).rotate((num*(360/10))+(self.condition*23))
line = line*self.radius
pygame.gfxdraw.line(screen, int(self.x), int(self.y), int(self.x+line[0]), int(self.y+line[1]), self.color)
def print_self(self):
#diagnostic
print("==============")
print("radius:", self.radius)
print("color:", self.color)
print("linear_speed:", self.linear_speed)
print("angular_speed:", self.angular_speed)
print("x:", self.x)
print("y:", int(self.y))
print("orientation:", self.orientation)
def avoid_others(self, _flock):
for _critter in _flock:
#if the critter isn't ME...
if _critter.GUID is not self.GUID and _critter.condition == 0:
#and it's touching me...
if self.x - _critter.x <= self.radius + _critter.radius:
me = Vector(self.x, int(self.y))
other_guy = Vector(_critter.x, _critter.y)
distance = me - other_guy
#give me new orientation that's away from the other guy
if distance.norm() <= ((self.radius) + (_critter.radius)):
new_direction = me - other_guy
self.orientation = self.new_orientation = new_direction.normalize()
def update_location(self, elapsed):
boundary = '?'
while boundary != 'X':
boundary = self.out_of_bounds()
if boundary == 'N':
self.orientation = self.new_orientation = Vector(0, 1).rotate(random.randint(-20, 20))
self.y = (self.radius) + 2
elif boundary == 'S':
self.orientation = self.new_orientation = Vector(0,-1).rotate(random.randint(-20, 20))
self.y = (size_y - (self.radius)) - 2
elif boundary == 'E':
self.orientation = self.new_orientation = Vector(-1,0).rotate(random.randint(-20, 20))
self.x = (size_x - (self.radius)) - 2
elif boundary == 'W':
self.orientation = self.new_orientation = Vector(1,0).rotate(random.randint(-20, 20))
self.x = (self.radius) + 2
point = Vector(self.x, self.y)
self.x, self.y = (point + (self.orientation * (self.linear_speed*(elapsed/1000))))
boundary = self.out_of_bounds()
def update_orientation(self, elapsed):
#randomly choose a new direction, from time to time
if random.randint(0, 100) > 98:
self.choose_new_orientation()
difference = self.orientation.argument() - self.new_orientation.argument()
self.orientation = self.orientation.rotate((difference * (self.angular_speed*(elapsed/1000))))
def still_alive(self, elapsed):
return_value = True #I am still alive
if self.condition == 0:
return_value = True
elif self.condition <= FRAMERATE*SECS_FOR_DYING:
self.condition = self.condition + (elapsed/17)
return_value = True
if self.condition > FRAMERATE*SECS_FOR_DYING:
return_value = False
return return_value
def choose_new_orientation(self):
if self.new_orientation:
if (self.orientation.argument() - self.new_orientation.argument()) < 5:
rotation = random.randint(-300, 300)
self.new_orientation = self.orientation.rotate(rotation)
def out_of_bounds(self):
if self.x >= (size_x - (self.radius)):
return 'E'
elif self.y >= (size_y - (self.radius)):
return 'S'
elif self.x <= (0 + (self.radius)):
return 'W'
elif self.y <= (0 + (self.radius)):
return 'N'
else:
return 'X'
# -------- Main Program Loop -----------
# generate critters
flock = [Critter()]
# generate heat map
heatMap = HeatMap(60, 40)
heatMap.make_map()
# set some settings
last_spawn = time.clock()
run_time = time.perf_counter()
frame_count = 0
max_time = 0
ms_elapsed = 1
avg_fps = [1]
# Loop until the user clicks the close button.
done = False
while not done:
# --- Main event loop only processes one event
frame_count = frame_count + 1
for event in pygame.event.get():
if event.type == pygame.QUIT:
done = True
# --- Game logic should go here
#check if it's time to make another critter
if time.clock() - last_spawn > SPAWN_TIME:
flock.append(Critter())
last_spawn = time.clock()
if len(flock) >= FLOCK_LIMIT:
#if we're over the flock limit, cull the herd
counter = FLOCK_LIMIT
for critter in flock[0:len(flock)-FLOCK_LIMIT]:
#this code allows a critter to be "dying" for a while, to play an animation
if critter.condition == 0:
critter.condition = 1
elif not critter.still_alive(ms_elapsed):
critter.delete_me = True
counter = 0
#delete all the critters that have finished dying
while counter < len(flock):
if flock[counter].delete_me:
del flock[counter]
else:
counter = counter+1
#----loop on all critters once, doing all functions for each critter
for critter in flock:
if critter.condition == 0:
critter.avoid_others(flock)
if critter.condition == 0:
heatMap.register(critter.x, critter.y)
critter.update_location(ms_elapsed)
critter.update_orientation(ms_elapsed)
if diagnostic:
critter.print_self()
#----alternately, loop for each function. Speed seems to be similar either way
#for critter in flock:
# if critter.condition == 0:
# critter.update_location(ms_elapsed)
#for critter in flock:
# if critter.condition == 0:
# critter.update_orientation(ms_elapsed)
# --- Screen-clearing code goes here
# Here, we clear the screen to white. Don't put other drawing commands
screen.fill(WHITE)
# --- Drawing code should go here
#draw the heat_map
heatMap.hm_draw_self()
for critter in flock:
critter.c_draw_self()
#draw the framerate
myfont = pygame.font.SysFont("monospace", 15)
#average the framerate over 60 frames
temp = sum(avg_fps)/float(len(avg_fps))
text = str(round(((1/temp)*1000),0))+"FPS | "+str(len(flock))+" Critters"
label = myfont.render(text, 1, (0, 0, 0))
screen.blit(label, (5, 5))
# --- Go ahead and update the screen with what we've drawn.
pygame.display.update()
# --- Limit to 60 frames per second
#only run for 30 seconds
if time.perf_counter()-run_time >= 30:
done = True
#limit to 60fps
#add this frame's time to the list
avg_fps.append(ms_elapsed)
#remove any old frames
while len(avg_fps) > 60:
del avg_fps[0]
ms_elapsed = clock.tick(FRAMERATE)
#track longest frame
if ms_elapsed > max_time:
max_time = ms_elapsed
#print some stats once the program is finished
print("Count:", frame_count)
print("Max time since last flip:", str(max_time)+"ms")
print("Total Time:", str(int(time.perf_counter()-run_time))+"s")
print("Average time for a flip:", str(int(((time.perf_counter()-run_time)/frame_count)*1000))+"ms")
# Close the window and quit.
pygame.quit()
One thing you can already do to improve the performance is to use pygame.math.Vector2 instead of your Vector class, because it's implemented in C and therefore faster. Before I switched to pygame's vector class, I could have ~50 critters on the screen before the frame rate dropped below 60, and after the change up to ~100.
pygame.math.Vector2 doesn't have that argument method, so you need to extract it from the class and turn it into a function:
def argument(vec):
""" Returns the argument of the vector, the angle clockwise from +y."""
arg_in_rad = math.acos(Vector(0,1)*vec/vec.length())
arg_in_deg = math.degrees(arg_in_rad)
if vec.x < 0:
return 360 - arg_in_deg
else:
return arg_in_deg
And change .norm() to .length() everywhere in the program.
Also, define the font object (myfont) before the while loop. That's only a minor improvement, but every frame counts.
Another change that made a significant improvement was to streamline my collision-detection algorithm.
Formerly, I had been looping through every critter in the flock, and measuring the distance between it and every other critter in the flock. If that distance was small enough, I do something. That's n^2 checks, which is not awesome.
I'd thought about using a quadtree, but it didn't seem efficient to rebalance the whole tree every frame, because it will change every time a critter moves.
Well, I finally actually tried it, and it turns out that building a brand-new quadtree at the beginning of each frame is actually plenty fast. Once I have the tree, I pass it to the avoidance function where I just extract an intersection of any of the critters in that tree within a bounding box I care about. Then I just iterate on those neighbors to measure distances and update directions and whatnot.
Now I'm up to 150 or so critters before I start dropping frames (up from 40).
So the moral of the story is, trust evidence instead of intuition.