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Create mqtt_pump_focus_image_segment_strem.py

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tpollina 2020-02-04 21:00:12 -08:00 committed by GitHub
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################################################################################
#Actuator Libraries
################################################################################
#Library for exchaning messages with Node-RED
import paho.mqtt.client as mqtt
#Library to control the PiCamera
from picamera import PiCamera
#Libraries to control the steppers for focusing and pumping
from adafruit_motor import stepper
from adafruit_motorkit import MotorKit
#Library to send command over I2C for the light module on the fan
import smbus
################################################################################
#Practical Libraries
################################################################################
#Library to get date and time for folder name and filename
from datetime import datetime, timedelta
#Library to be able to sleep for a duration
from time import sleep
#Libraries manipulate json format, execute bash commands
import json, shutil, os, subprocess
################################################################################
#Morphocut Libraries
################################################################################
from skimage.util import img_as_ubyte
from morphocut import Call
from morphocut.contrib.ecotaxa import EcotaxaWriter
from morphocut.contrib.zooprocess import CalculateZooProcessFeatures
from morphocut.core import Pipeline
from morphocut.file import Find
from morphocut.image import (ExtractROI,
FindRegions,
ImageReader,
ImageWriter,
RescaleIntensity,
RGB2Gray
)
from morphocut.stat import RunningMedian
from morphocut.str import Format
from morphocut.stream import TQDM, Enumerate, FilterVariables
################################################################################
#Other image processing Libraries
################################################################################
from skimage.feature import canny
from skimage.color import rgb2gray, label2rgb
from skimage.morphology import disk
from skimage.morphology import erosion, dilation, closing
from skimage.measure import label, regionprops
#pip3 install opencv-python
import cv2
################################################################################
#STREAMING
################################################################################
import io
import picamera
import logging
import socketserver
from threading import Condition
from http import server
import threading
PAGE="""\
<html>
<head>
<title>picamera MJPEG streaming demo</title>
</head>
<body>
<img src="stream.mjpg" width="640" height="480" />
</body>
</html>
"""
class StreamingOutput(object):
def __init__(self):
self.frame = None
self.buffer = io.BytesIO()
self.condition = Condition()
def write(self, buf):
if buf.startswith(b'\xff\xd8'):
# New frame, copy the existing buffer's content and notify all
# clients it's available
self.buffer.truncate()
with self.condition:
self.frame = self.buffer.getvalue()
self.condition.notify_all()
self.buffer.seek(0)
return self.buffer.write(buf)
class StreamingHandler(server.BaseHTTPRequestHandler):
def do_GET(self):
if self.path == '/':
self.send_response(301)
self.send_header('Location', '/index.html')
self.end_headers()
elif self.path == '/index.html':
content = PAGE.encode('utf-8')
self.send_response(200)
self.send_header('Content-Type', 'text/html')
self.send_header('Content-Length', len(content))
self.end_headers()
self.wfile.write(content)
elif self.path == '/stream.mjpg':
self.send_response(200)
self.send_header('Age', 0)
self.send_header('Cache-Control', 'no-cache, private')
self.send_header('Pragma', 'no-cache')
self.send_header('Content-Type', 'multipart/x-mixed-replace; boundary=FRAME')
self.end_headers()
try:
while True:
with output.condition:
output.condition.wait()
frame = output.frame
self.wfile.write(b'--FRAME\r\n')
self.send_header('Content-Type', 'image/jpeg')
self.send_header('Content-Length', len(frame))
self.end_headers()
self.wfile.write(frame)
self.wfile.write(b'\r\n')
except Exception as e:
logging.warning(
'Removed streaming client %s: %s',
self.client_address, str(e))
else:
self.send_error(404)
self.end_headers()
class StreamingServer(socketserver.ThreadingMixIn, server.HTTPServer):
allow_reuse_address = True
daemon_threads = True
################################################################################
#MQTT core functions
################################################################################
#Run this function in order to connect to the client (Node-RED)
def on_connect(client, userdata, flags, rc):
#Print when connected
print("Connected! - " + str(rc))
#When connected, run subscribe()
client.subscribe("actuator/#")
#Turn green the light module
rgb(0,255,0)
#Run this function in order to subscribe to all the topics begining by actuator
def on_subscribe(client, obj, mid, granted_qos):
#Print when subscribed
print("Subscribed! - "+str(mid)+" "+str(granted_qos))
#Run this command when Node-RED is sending a message on the subscribed topic
def on_message(client, userdata, msg):
#Print the topic and the message
print(msg.topic+" "+str(msg.qos)+" "+str(msg.payload))
#Update the global variables command, args and counter
global command
global args
global counter
#Parse the topic to find the command. ex : actuator/pump -> pump
command=msg.topic.split("/")[1]
#Decode the message to find the arguments
args=str(msg.payload.decode())
#Reset the counter to 0
counter=0
################################################################################
#Actuators core functions
################################################################################
def rgb(R,G,B):
#Update LED n°1
bus.write_byte_data(0x0d, 0x00, 0)
bus.write_byte_data(0x0d, 0x01, R)
bus.write_byte_data(0x0d, 0x02, G)
bus.write_byte_data(0x0d, 0x03, B)
#Update LED n°2
bus.write_byte_data(0x0d, 0x00, 1)
bus.write_byte_data(0x0d, 0x01, R)
bus.write_byte_data(0x0d, 0x02, G)
bus.write_byte_data(0x0d, 0x03, B)
#Update LED n°3
bus.write_byte_data(0x0d, 0x00, 2)
bus.write_byte_data(0x0d, 0x01, R)
bus.write_byte_data(0x0d, 0x02, G)
bus.write_byte_data(0x0d, 0x03, B)
#Update the I2C Bus in order to really update the LEDs new values
cmd="i2cdetect -y 1"
subprocess.Popen(cmd.split(),stdout=subprocess.PIPE)
################################################################################
#Init function - executed only once
################################################################################
#define the bus used to actuate the light module on the fan
bus = smbus.SMBus(1)
#define the names for the 2 exsting steppers
kit = MotorKit()
pump_stepper = kit.stepper1
pump_stepper.release()
focus_stepper = kit.stepper2
focus_stepper.release()
#Precise the settings of the PiCamera
camera = PiCamera()
camera.resolution = (3280, 2464)
camera.iso = 60
camera.shutter_speed = 500
camera.exposure_mode = 'fixedfps'
#Declare the global variables command, args and counter
command = ''
args = ''
counter=''
client = mqtt.Client()
client.connect("127.0.0.1",1883,60)
client.on_connect = on_connect
client.on_subscribe = on_subscribe
client.on_message = on_message
client.loop_start()
################################################################################
local_metadata = {
"process_datetime": datetime.now(),
"acq_camera_resolution" : camera.resolution,
"acq_camera_iso" : camera.iso,
"acq_camera_shutter_speed" : camera.shutter_speed
}
config_txt = open('/home/pi/PlanktonScope/config.txt','r')
node_red_metadata = json.loads(config_txt.read())
global_metadata = {**local_metadata, **node_red_metadata}
archive_fn = os.path.join("/home/pi/PlanktonScope/","export", "ecotaxa_export.zip")
# Define processing pipeline
with Pipeline() as p:
# Recursively find .jpg files in import_path.
# Sort to get consective frames.
abs_path = Find("/home/pi/PlanktonScope/tmp", [".jpg"], sort=True, verbose=True)
# Extract name from abs_path
name = Call(lambda p: os.path.splitext(os.path.basename(p))[0], abs_path)
Call(rgb, 0,255,0)
# Read image
img = ImageReader(abs_path)
# Show progress bar for frames
TQDM(Format("Frame {name}", name=name))
# Apply running median to approximate the background image
flat_field = RunningMedian(img, 5)
# Correct image
img = img / flat_field
# Rescale intensities and convert to uint8 to speed up calculations
img = RescaleIntensity(img, in_range=(0, 1.1), dtype="uint8")
FilterVariables(name,img)
# frame_fn = Format(os.path.join("/home/pi/PlanktonScope/tmp","CLEAN", "{name}.jpg"), name=name)
# ImageWriter(frame_fn, img)
# Convert image to uint8 gray
img_gray = RGB2Gray(img)
# ?
img_gray = Call(img_as_ubyte, img_gray)
#Canny edge detection
img_canny = Call(cv2.Canny, img_gray, 50,100)
#Dilate
kernel = Call(cv2.getStructuringElement, cv2.MORPH_ELLIPSE, (15, 15))
img_dilate = Call(cv2.dilate, img_canny, kernel, iterations=2)
#Close
kernel = Call(cv2.getStructuringElement, cv2.MORPH_ELLIPSE, (5, 5))
img_close = Call(cv2.morphologyEx, img_dilate, cv2.MORPH_CLOSE, kernel, iterations=1)
#Erode
kernel = Call(cv2.getStructuringElement, cv2.MORPH_ELLIPSE, (15, 15))
mask = Call(cv2.erode, img_close, kernel, iterations=2)
# Find objects
regionprops = FindRegions(
mask, img_gray, min_area=1000, padding=10, warn_empty=name
)
Call(rgb, 255,0,255)
# For an object, extract a vignette/ROI from the image
roi_orig = ExtractROI(img, regionprops, bg_color=255)
# Generate an object identifier
i = Enumerate()
#Call(print,i)
object_id = Format("{name}_{i:d}", name=name, i=i)
#Call(print,object_id)
object_fn = Format(os.path.join("/home/pi/PlanktonScope/","OBJECTS", "{name}.jpg"), name=object_id)
ImageWriter(object_fn, roi_orig)
# Calculate features. The calculated features are added to the global_metadata.
# Returns a Variable representing a dict for every object in the stream.
meta = CalculateZooProcessFeatures(
regionprops, prefix="object_", meta=global_metadata
)
json_meta = Call(json.dumps,meta, sort_keys=True, default=str)
Call(client.publish, "receiver/segmentation/metric", json_meta)
# Add object_id to the metadata dictionary
meta["object_id"] = object_id
# Generate object filenames
orig_fn = Format("{object_id}.jpg", object_id=object_id)
# Write objects to an EcoTaxa archive:
# roi image in original color, roi image in grayscale, metadata associated with each object
EcotaxaWriter(archive_fn, (orig_fn, roi_orig), meta)
# Progress bar for objects
TQDM(Format("Object {object_id}", object_id=object_id))
Call(client.publish, "receiver/segmentation/object_id", object_id)
output = StreamingOutput()
address = ('', 8000)
server = StreamingServer(address, StreamingHandler)
threading.Thread(target=server.serve_forever).start()
################################################################################
camera.start_recording(output, format='mjpeg', resize=(640, 480))
while True:
if (command=="pump"):
rgb(0,0,255)
direction=args.split(" ")[0]
delay=float(args.split(" ")[1])
nb_step=int(args.split(" ")[2])
client.publish("receiver/pump", "Start");
while True:
if direction == "BACKWARD":
direction=stepper.BACKWARD
if direction == "FORWARD":
direction=stepper.FORWARD
pump_stepper.onestep(direction=direction, style=stepper.DOUBLE)
counter+=1
sleep(delay)
if command!="pump":
pump_stepper.release()
print("The pump has been interrompted.")
client.publish("receiver/pump", "Interrompted");
rgb(0,255,0)
break
if counter>nb_step:
pump_stepper.release()
print("The pumping is done.")
command="wait"
client.publish("receiver/pump", "Done");
rgb(0,255,0)
break
################################################################################
elif (command=="focus"):
rgb(255,255,0)
direction=args.split(" ")[0]
nb_step=int(args.split(" ")[1])
client.publish("receiver/focus", "Start");
while True:
if direction == "FORWARD":
direction=stepper.FORWARD
if direction == "BACKWARD":
direction=stepper.BACKWARD
counter+=1
focus_stepper.onestep(direction=direction, style=stepper.MICROSTEP)
if command!="focus":
focus_stepper.release()
print("The stage has been interrompted.")
client.publish("receiver/focus", "Interrompted");
rgb(0,255,0)
break
if counter>nb_step:
focus_stepper.release()
print("The focusing is done.")
command="wait"
client.publish("receiver/focus", "Done");
rgb(0,255,0)
break
################################################################################
elif (command=="image"):
sleep_before=int(args.split(" ")[0])
nb_step=int(args.split(" ")[1])
path=str(args.split(" ")[2])
nb_frame=int(args.split(" ")[3])
sleep_during=int(args.split(" ")[4])
#sleep a duration before to start
sleep(sleep_before)
client.publish("receiver/image", "Start");
#flushing before to begin
rgb(0,0,255)
for i in range(nb_step):
if (command=="image"):
pump_stepper.onestep(direction=stepper.FORWARD, style=stepper.DOUBLE)
sleep(0.01)
else:
break
rgb(0,255,0)
while True:
counter+=1
print(datetime.now().strftime("%H_%M_%S_%f"))
filename = os.path.join("/home/pi/PlanktonScope/tmp",datetime.now().strftime("%M_%S_%f")+".jpg")
rgb(0,255,255)
camera.capture(filename)
rgb(0,255,0)
client.publish("receiver/image", datetime.now().strftime("%M_%S_%f")+".jpg has been imaged.");
rgb(0,0,255)
for i in range(10):
pump_stepper.onestep(direction=stepper.FORWARD, style=stepper.DOUBLE)
sleep(0.01)
sleep(0.5)
rgb(0,255,0)
if(counter>nb_frame):
# camera.stop_preview()
client.publish("receiver/image", "Completed");
# Meta data that is added to every object
client.publish("receiver/segmentation", "Start");
# Define processing pipeline
p.run()
#remove directory
#shutil.rmtree(import_path)
client.publish("receiver/segmentation", "Completed");
cmd = os.popen("rm -rf /home/pi/PlanktonScope/tmp/*.jpg")
rgb(255,255,255)
sleep(sleep_during)
rgb(0,255,0)
rgb(0,0,255)
for i in range(nb_step):
pump_stepper.onestep(direction=stepper.FORWARD, style=stepper.DOUBLE)
sleep(0.01)
rgb(0,255,0)
counter=0
if command!="image":
pump_stepper.release()
print("The imaging has been interrompted.")
client.publish("receiver/image", "Interrompted");
rgb(0,255,0)
counter=0
break
else:
# print("Waiting")
sleep(1)