Merge remote-tracking branch 'thibault/master'
Update to the README merged accordingly
This commit is contained in:
Romain Bazile
commit
d289f28aa3
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README.md
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README.md
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@ -1,13 +1,15 @@
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||||||
# PlanktoScop Main Repository
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# PlanktoScop Main Repository
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The PlanktoScop is an open and affordable modular imaging platform for citizen oceanography.
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The PlanktoScop is an open and affordable modular imaging platform for citizen oceanography.
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||||||
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||||||
It's a high-throughtput microscope platform, designed with an open-hardware and open-software mentality.
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This GitHub is part of a community that you can find on [its website](https://www.planktonscope.org/).
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||||||
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||||||
You can learn more about the PlantoScop [on its website](https://www.planktonscope.org/discover).
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# Fast Setup
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Before going further, notice that you can download the image disk already setup without having to deal with all these command lines.
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Jump here : http://planktonscope.su.domains/Images_raspberry/Raspbian_Buster_Morphocut_WiFi.img
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# PlanktoScop Raspberry Pi Setup
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# Expert Setup
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After getting your kit and finding the necessary components, but before assembling your kit, you should take the time to do a mockup build and setup your Raspberry!
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After getting your kit and finding the necessary components, but before assembling your kit, you should take the time to do a mockup build and setup your Raspberry.
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||||||
## Install and setup Raspbian on your Raspberry Pi
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## Install and setup Raspbian on your Raspberry Pi
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@ -197,13 +199,13 @@ https://www.pyimagesearch.com/2019/09/16/install-opencv-4-on-raspberry-pi-4-and-
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### Install MorphoCut
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### Install MorphoCut
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[Installing MorphoCut](https://morphocut.readthedocs.io/en/stable/installation.html)
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||||||
_Installing MorphoCut <https://morphocut.readthedocs.io/en/stable/installation.html>`_
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||||||
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||||||
MorphoCut is packaged on PyPI and can be installed with pip:
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MorphoCut is packaged on PyPI and can be installed with pip:
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```
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```sh
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sudo apt-get install python3-scipy
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sudo apt-get install python3-scipy
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pip3 install -U git+https://github.com/morphocut/morphocut.git@pyrocystis
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pip3 install -U git+https://github.com/morphocut/morphocut.git
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```
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```
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||||||
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||||||
## Finishing the install
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## Finishing the install
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||||||
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theme: jekyll-theme-minimal
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|
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File diff suppressed because it is too large
Load diff
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Load diff
|
|
@ -1,140 +0,0 @@
|
||||||
|
|
||||||
import datetime
|
|
||||||
import os
|
|
||||||
|
|
||||||
from skimage.util import img_as_ubyte
|
|
||||||
from skimage.filters import threshold_otsu
|
|
||||||
|
|
||||||
|
|
||||||
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
|
|
||||||
|
|
||||||
import_path = "/home/pi/Desktop/PlanktonScope_acquisition/01_17_2020/16_2"
|
|
||||||
export_path = "/home/pi/Desktop/PlanktonScope_acquisition/01_17_2020/16"
|
|
||||||
archive_fn = os.path.join(export_path, "17_morphocut_processed.zip")
|
|
||||||
|
|
||||||
# Meta data that is added to every object
|
|
||||||
global_metadata = {
|
|
||||||
"process_datetime": datetime.datetime.now(),
|
|
||||||
"sample_project": "PlanktonScope Villefranche",
|
|
||||||
"sample_ship": "Kayak de Fabien",
|
|
||||||
"sample_operator": "Thibaut Pollina",
|
|
||||||
"sample_id": "Flowcam_PlanktonScope_comparison",
|
|
||||||
"sample_sampling_gear": "net",
|
|
||||||
"object_date": 20200117,
|
|
||||||
"object_time": 150000,
|
|
||||||
"object_lat": 43.696146,
|
|
||||||
"object_lon": 7.308359,
|
|
||||||
"object_depth_min": 0,
|
|
||||||
"object_depth_max": 1,
|
|
||||||
"acq_fnumber_objective": 16,
|
|
||||||
"acq_celltype": 400,
|
|
||||||
"acq_camera": "Pi Camera V2.1",
|
|
||||||
"acq_instrument": "PlanktonScope V2.1",
|
|
||||||
"acq_software": "Node-RED Dashboard and raw python",
|
|
||||||
"acq_instrument_ID": "copepode",
|
|
||||||
"acq_camera_resolution" : "(3280, 2464)",
|
|
||||||
"acq_camera_iso" : 60,
|
|
||||||
"acq_camera_shutter_speed" : 100,
|
|
||||||
"acq_camera_exposure_mode" : "off",
|
|
||||||
"acq_camera_awb_mode" : "off",
|
|
||||||
"process_pixel": 1.19
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
print("Processing images under {}...".format(import_path))
|
|
||||||
|
|
||||||
# Create export_path in case it doesn't exist
|
|
||||||
|
|
||||||
os.makedirs(export_path, exist_ok=True)
|
|
||||||
# Define processing pipeline
|
|
||||||
with Pipeline() as p:
|
|
||||||
# Recursively find .jpg files in import_path.
|
|
||||||
# Sort to get consective frames.
|
|
||||||
abs_path = Find(import_path, [".jpg"], sort=True, verbose=True)
|
|
||||||
|
|
||||||
# Extract name from abs_path
|
|
||||||
name = Call(lambda p: os.path.splitext(os.path.basename(p))[0], abs_path)
|
|
||||||
|
|
||||||
# Show progress bar for frames
|
|
||||||
TQDM(Format("Frame {name}", name=name))
|
|
||||||
|
|
||||||
# Read image
|
|
||||||
img = ImageReader(abs_path)
|
|
||||||
|
|
||||||
|
|
||||||
# Convert image to uint8 gray
|
|
||||||
img_gray = RGB2Gray(img)
|
|
||||||
|
|
||||||
#img_gray = Call(img_as_ubyte, img_gray)
|
|
||||||
|
|
||||||
# Apply threshold find objects
|
|
||||||
|
|
||||||
#threshold = 200 #
|
|
||||||
#threshold = Call(threshold_otsu, img_gray)
|
|
||||||
threshold = 180 #
|
|
||||||
|
|
||||||
mask = img_gray < threshold
|
|
||||||
|
|
||||||
|
|
||||||
# Write corrected frames
|
|
||||||
|
|
||||||
ImageWriter(frame_fn, mask)
|
|
||||||
|
|
||||||
# Find objects
|
|
||||||
regionprops = FindRegions(
|
|
||||||
mask, img_gray, min_area=300, padding=10, warn_empty=name
|
|
||||||
)
|
|
||||||
|
|
||||||
# For an object, extract a vignette/ROI from the image
|
|
||||||
roi_orig = ExtractROI(img, regionprops, bg_color=255)
|
|
||||||
#roi_gray = ExtractROI(img_gray, regionprops, bg_color=255)
|
|
||||||
|
|
||||||
# Generate an object identifier
|
|
||||||
i = Enumerate()
|
|
||||||
|
|
||||||
object_id = Format("{name}_{i:d}", name=name, i=i)
|
|
||||||
|
|
||||||
# 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
|
|
||||||
#)
|
|
||||||
# If CalculateZooProcessFeatures is not used, we need to copy global_metadata into the stream:
|
|
||||||
# meta = Call(lambda: global_metadata.copy())
|
|
||||||
# https://github.com/morphocut/morphocut/issues/51
|
|
||||||
|
|
||||||
# Add object_id to the metadata dictionary
|
|
||||||
#meta["object_id"] = object_id
|
|
||||||
|
|
||||||
# Generate object filenames
|
|
||||||
|
|
||||||
orig_fn = Format(os.path.join(export_path, "{object_id}.jpg"), object_id=object_id)
|
|
||||||
#gray_fn = Format("{object_id}-gray.jpg", object_id=object_id)
|
|
||||||
|
|
||||||
ImageWriter(orig_fn, roi_orig)
|
|
||||||
|
|
||||||
# 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))
|
|
||||||
|
|
||||||
# Execute pipeline
|
|
||||||
p.run()
|
|
||||||
|
|
@ -1,116 +0,0 @@
|
||||||
#!/usr/bin/env python
|
|
||||||
# coding: utf-8
|
|
||||||
|
|
||||||
################################################################################
|
|
||||||
# A) Import the librairies needed to execute the script
|
|
||||||
################################################################################
|
|
||||||
#Activate pinout to control the LEDs and the RELAY
|
|
||||||
from gpiozero import LED
|
|
||||||
#Allow to access the I2C BUS from the Raspberry Pi
|
|
||||||
import smbus
|
|
||||||
#Time librairy in order to sleep when need
|
|
||||||
from time import sleep
|
|
||||||
#Picamera library to take images
|
|
||||||
from picamera import PiCamera
|
|
||||||
#Enable calculation of remaining duration and datetime
|
|
||||||
from datetime import datetime, timedelta
|
|
||||||
#Enable creation of new folders
|
|
||||||
import os
|
|
||||||
from adafruit_motor import stepper
|
|
||||||
from adafruit_motorkit import MotorKit
|
|
||||||
from time import sleep
|
|
||||||
|
|
||||||
kit = MotorKit()
|
|
||||||
pump_stepper = kit.stepper1
|
|
||||||
pump_stepper.release()
|
|
||||||
|
|
||||||
|
|
||||||
################################################################################
|
|
||||||
# C) Configuration file
|
|
||||||
################################################################################
|
|
||||||
|
|
||||||
|
|
||||||
camera = PiCamera()
|
|
||||||
camera.resolution = (3280, 2464)
|
|
||||||
camera.iso = 60
|
|
||||||
sleep(3)
|
|
||||||
camera.shutter_speed = 300
|
|
||||||
camera.exposure_mode = 'off'
|
|
||||||
g = camera.awb_gains
|
|
||||||
camera.awb_mode = 'off'
|
|
||||||
camera.awb_gains = g
|
|
||||||
nb_frame=2000
|
|
||||||
|
|
||||||
pump_stepper.release()
|
|
||||||
################################################################################
|
|
||||||
# E) Define simple functions making the whole sequence
|
|
||||||
###
|
|
||||||
|
|
||||||
################################################################################
|
|
||||||
|
|
||||||
|
|
||||||
print("###############")
|
|
||||||
print("IMAGING")
|
|
||||||
print("###############")
|
|
||||||
|
|
||||||
#Inform on the statut of the operation
|
|
||||||
print("Imaging : engaged")
|
|
||||||
#start the preview only during the acquisition
|
|
||||||
camera.start_preview(fullscreen=False, window = (160, 0, 640, 480))
|
|
||||||
|
|
||||||
|
|
||||||
#get the actual date
|
|
||||||
date_now = datetime.now().strftime("%m_%d_%Y")
|
|
||||||
day_now="/home/pi/Desktop/PlanktonScope_acquisition/"+str(date_now)
|
|
||||||
|
|
||||||
#create a directory if the directory doesn't exist yet
|
|
||||||
if not os.path.exists(day_now):
|
|
||||||
os.makedirs(day_now)
|
|
||||||
|
|
||||||
#get the actual date
|
|
||||||
hour_now = datetime.now().strftime("%H")
|
|
||||||
hour="/home/pi/Desktop/PlanktonScope_acquisition/"+str(date_now)+"/"+str(hour_now)
|
|
||||||
|
|
||||||
#create a directory if the directory doesn't exist yet
|
|
||||||
if not os.path.exists(hour):
|
|
||||||
os.makedirs(hour)
|
|
||||||
|
|
||||||
|
|
||||||
#allow the camera to warm up
|
|
||||||
|
|
||||||
for i in range(200):
|
|
||||||
pump_stepper.onestep(direction=stepper.BACKWARD, style=stepper.SINGLE)
|
|
||||||
sleep(0.01)
|
|
||||||
|
|
||||||
for frame in range(nb_frame):
|
|
||||||
|
|
||||||
#get the time now
|
|
||||||
time = datetime.now().strftime("%M_%S_%f")
|
|
||||||
#create a filename from the date and the time
|
|
||||||
filename="/home/pi/Desktop/PlanktonScope_acquisition/"+str(date_now)+"/"+str(hour_now)+"/"+str(time)+".jpg"
|
|
||||||
|
|
||||||
#capture an image with the specified filename
|
|
||||||
camera.capture(filename)
|
|
||||||
|
|
||||||
#wait to complete the imaging process and print info on the terminal
|
|
||||||
print("Imaging : "+str(frame)+"/"+str(nb_frame))
|
|
||||||
|
|
||||||
for i in range(10):
|
|
||||||
pump_stepper.onestep(direction=stepper.BACKWARD, style=stepper.SINGLE)
|
|
||||||
sleep(0.01)
|
|
||||||
sleep(0.5)
|
|
||||||
|
|
||||||
|
|
||||||
#stop the preview during the rest of the sequence
|
|
||||||
camera.stop_preview()
|
|
||||||
pump_stepper.release()
|
|
||||||
|
|
||||||
#Inform on the statut of the operation
|
|
||||||
print("Imaging : done")
|
|
||||||
|
|
||||||
|
|
||||||
################################################################################
|
|
||||||
|
|
||||||
#################################################
|
|
||||||
# F) Execute the sequence
|
|
||||||
################################################################################
|
|
||||||
Loading…
Reference in a new issue