first commit. Code for doing low cost image analysis with Raspberry Pi.

README.md

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+This is a repo for doing some basic colout analysis with a Raspberry Pi and some extra webcams. 
+
+

binary.csv

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+2019-07-09-112544, 0 
+2019-07-09-112545, 0 
+2019-07-09-113009, 0 
+2019-07-09-113011, 0 
+2019-07-09-113052, 0 
+2019-07-09-113053, 0 
+2019-07-09-113904, 0 
+2019-07-09-113906, 0 
+2019-07-09-114437, 0 
+2019-07-09-114438, 0 
+2019-07-09-114536, 0 
+2019-07-09-114538, 0 
+2019-07-09-114705, 0 
+2019-07-09-114707, 0 
+2019-07-09-114830, 0 
+2019-07-09-114832, 0 
+2019-07-09-115134, 0 
+2019-07-09-115136, 0 
+2019-07-09-115358, 0 
+2019-07-09-115359, 0 
+2019-07-09-115603, 0 
+2019-07-09-115604, 0 
+2019-07-09-115741, 0 
+2019-07-09-115743, 0 
+2019-07-09-120010, 1 
+2019-07-09-120012, 1 
+2019-07-09-120844, 0 
+2019-07-09-120845, 0 

color_analysis.py

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+# From https://www.pyimagesearch.com/2014/08/04/opencv-python-color-detection/
+# import the necessary packages
+import sys
+sys.path.append('/home/pi/.local/lib/python3.5/site-packages')
+import numpy as np
+import argparse
+import cv2
+import datetime
+# construct the argument parse and parse the arguments
+ap = argparse.ArgumentParser()
+ap.add_argument("-i", "--image", help = "path to the image")
+args = vars(ap.parse_args())
+# load the image
+image = cv2.imread(args["image"])
+# define the list of boundaries
+boundaries = [
+    ([0, 0, 10], [50, 50, 255])
+]
+# loop over the boundaries
+for (lower, upper) in boundaries:
+    # create NumPy arrays from the boundaries
+    lower = np.array(lower, dtype = "uint8")
+    upper = np.array(upper, dtype = "uint8")
+    # find the colors within the specified boundaries and apply
+    # the mask
+    mask = cv2.inRange(image, lower, upper)
+    output = cv2.bitwise_and(image, image, mask = mask)
+
+    # Save the images
+    timenow = datetime.datetime.now()
+    filename1 = timenow.strftime("%Y-%m-%d-%H%M%S")
+    cv2.imwrite(filename1+".jpg", output)   # Or np.hstack([image,output])
+    #cv2.waitKey(0)
+    output_max = np.max(output)
+    output_min = np.min(output)
+    output_norm = (output - output_min)/(output_max - output_min)
+    total_pixels = output_norm.shape[0]*output_norm.shape[1]
+    abovethreshold_pixels = (output_norm > 1).sum()
+    norm_abovethreshold = (abovethreshold_pixels/total_pixels)*100
+    print(total_pixels, abovethreshold_pixels, norm_abovethreshold )
+    if norm_abovethreshold > 10:
+        print (filename1, "Red in frame")
+	f = open('binary.csv','a')
+	f.write(filename1+', 1 \n') #Give your csv text here.
+	## Python will convert \n to os.linesep
+	f.close()
+    elif norm_abovethreshold <= 10:
+        print (filename1, "NO Red in frame")
+	f = open('binary.csv','a')
+        f.write(filename1+', 0 \n') #Give your csv text here.
+        ## Python will convert \n to os.linesep
+        f.close()

image_analysis.py

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+from clarifai.rest import ClarifaiApp
+
+image_directory = '/home/pi/webcam/cam1/'
+
+app = ClarifaiApp(api_key='40d74b5ce16b47d794ee6b6955f7f930')
+model = app.public_models.general_model
+##response = model.predict_by_url('https://samples.clarifai.com/metro-north.jpg')
+#response = model.predict_by_url('https://gb.gilson.com/pub/media/catalog/product/cache/c687aa7517cf01e65c009f6943c2b1e9/F/1/F123603_MAIN_Pipetman-Classic-Single-Channel-Pipette-P5000_8.jpg')
+response = model.predict_by_filename(image_directory+'2019-06-05_140044.jpg')
+
+concepts = response['outputs'][0]['data']['concepts']
+for concept in concepts:
+    print(concept['name'], concept['value'])

image_segment.sh

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+#!/bin/bash
+DATE=$(date +"%Y-%m-%d_%H%M%S")
+
+# This handy command will simply delay the next command by a specified interval
+echo "sleeping"
+ sleep 1
+echo "done sleeping"
+
+# This takes two photos and stores them in respective folders for each cam
+ sudo fswebcam -d /dev/video0 -r 352x288 --no-banner /home/pi/webcam/cam1/$DATE.jpg
+ sudo fswebcam -d /dev/video2 -r 352x288 --no-banner /home/pi/webcam/cam2/$DATE.jpg
+
+python /home/pi/webcam/color_analysis.py --image /home/pi/webcam/cam1/$DATE.jpg
+sudo rm /home/pi/webcam/cam1/$DATE.jpg
+mv /home/pi/webcam/2019* /home/pi/webcam/cam1/
+python /home/pi/webcam/color_analysis.py --image /home/pi/webcam/cam2/$DATE.jpg
+sudo rm /home/pi/webcam/cam2/$DATE.jpg
+mv /home/pi/webcam/2019*.jpg /home/pi/webcam/cam2/
+# This command places another image (with time banner) into a folder that streams to the web note the file location “../../var/www”
+ sudo fswebcam -d /dev/video0 -r 352x288 /var/www/webcam/cam1/timelapse.jpg
+ sudo fswebcam -d /dev/video2 -r 352x288 /var/www/webcam/cam2/timelapse.jpg
+
+# Now we use the convert command (see imagemagik) to creat gifs
+# The -delay gives the interval between picture changes and -loop sets it to repeat
+sudo convert -delay 20 -loop 0 /home/pi/webcam/cam1/*.jpg /home/pi/webcam/cam1/timelapse.gif
+sudo convert -delay 20 -loop 0 /home/pi/webcam/cam2/*.jpg /home/pi/webcam/cam2/timelapse.gif
+echo "creating gif"
+ # Now we copy these gifs to the webstream folder  “../../var/www”
+ sudo cp /home/pi/webcam/cam1/timelapse.gif /var/www/webcam/cam1/timelapse.gif
+ sudo cp /home/pi/webcam/cam2/timelapse.gif /var/www/webcam/cam2/timelapse.gif
+echo "copying gif to www folder!"
+echo "DONE"

webcam.sh

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+#!/bin/bash
+DATE=$(date +"%Y-%m-%d_%H%M%S")
+
+# This handy command will simply delay the next command by a specified interval
+echo "sleeping" 
+ sleep 1
+echo "done sleeping"
+
+# This takes two photos and stores them in respective folders for each cam
+ sudo fswebcam -d /dev/video0 -r 352x288 --no-banner /home/pi/webcam/cam1/$DATE.jpg
+ sudo fswebcam -d /dev/video2 -r 352x288 --no-banner /home/pi/webcam/cam2/$DATE.jpg
+
+# This command places another image (with time banner) into a folder that streams to the web note the file location “../../var/www”
+ sudo fswebcam -d /dev/video0 -r 352x288 /var/www/webcam/cam1/timelapse.jpg
+ sudo fswebcam -d /dev/video2 -r 352x288 /var/www/webcam/cam2/timelapse.jpg
+
+# Now we use the convert command (see imagemagik) to creat gifs
+# The -delay gives the interval between picture changes and -loop sets it to repeat
+sudo convert -delay 20 -loop 0 /home/pi/webcam/cam1/*.jpg /home/pi/webcam/cam1/timelapse.gif
+sudo convert -delay 20 -loop 0 /home/pi/webcam/cam2/*.jpg /home/pi/webcam/cam2/timelapse.gif
+echo "creating gif"
+ # Now we copy these gifs to the webstream folder  “../../var/www”
+ sudo cp /home/pi/webcam/cam1/timelapse.gif /var/www/webcam/cam1/timelapse.gif
+ sudo cp /home/pi/webcam/cam2/timelapse.gif /var/www/webcam/cam2/timelapse.gif
+echo "copying gif to www folder!"
+echo "DONE"