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107 lines
3.8 KiB
107 lines
3.8 KiB
#!/usr/bin/env python3
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import os
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from io import BytesIO
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import cv2
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import time
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import numpy as np
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import subprocess
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import logging
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import json
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import sys
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import paramiko
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import pysftp
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def main():
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import time as time1
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start = time1.time()
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cnopts = pysftp.CnOpts()
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cnopts.hostkeys = None
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try:
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sftp = pysftp.Connection(
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host="127.0.0.1",
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username="faasapp",
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password="1234",
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cnopts=cnopts
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)
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logging.info("connection established successfully")
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except:
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logging.info('failed to establish connection to targeted server')
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contour_directory = "contoured-images"
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is_contour_dir = os.path.isdir(contour_directory)
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if(is_contour_dir == False):
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os.mkdir(contour_directory)
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images_dir = "images"
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is_images_dir = os.path.isdir(images_dir)
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if(is_images_dir == False):
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os.mkdir(images_dir)
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remote_download_path = "/home/faasapp/Desktop/anubhav/sprocket-decode/"+images_dir
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remote_upload_path = "/home/faasapp/Desktop/anubhav/contour-finding/"+contour_directory
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try:
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sftp.chdir(remote_download_path) # Test if remote_path exists
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except IOError:
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sftp.mkdir(remote_download_path) # Create remote_path
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sftp.chdir(remote_download_path)
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try:
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sftp.chdir(remote_upload_path) # Test if remote_path exists
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except IOError:
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sftp.mkdir(remote_upload_path) # Create remote_path
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sftp.chdir(remote_upload_path)
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sftp.get_d(remote_download_path,preserve_mtime=True,localdir=images_dir)
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activation_id = os.environ.get('__OW_ACTIVATION_ID')
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params = json.loads(sys.argv[1])
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decode_activation_id = params["activation_id"]
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parts = params["parts"]
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image_contour_mappings = {}
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contour_detected_images = {}
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for i in range(0,parts):
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img_name = images_dir+'/Image' + str(i) + '.jpg'
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img = cv2.imread(img_name)
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img = cv2.resize(img,None,fx=0.9,fy=0.9)
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gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
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ret, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
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contours, hierarchy = cv2.findContours(binary, mode=cv2.RETR_TREE, method=cv2.CHAIN_APPROX_NONE)
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contour_list_for_each_image=[]
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cv2.drawContours(img, contours, -1, (0, 255, 0), thickness=2, lineType=cv2.LINE_AA)
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for contour in contours:
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approx = cv2.approxPolyDP(contour, 0.01* cv2.arcLength(contour, True), True)
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contour_list_for_each_image.append(len(approx))
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image_contour_mappings[img_name] = sum(contour_list_for_each_image)
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filename = 'contour' + str(i) +'.jpg'
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# Saving the image
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cv2.imwrite(contour_directory+"/"+filename, img)
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contour_img = cv2.imread(contour_directory+"/"+filename)
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# contour_height, contour_width = contour_img.shape[:2]
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contour_detected_size = os.stat(contour_directory+"/"+filename).st_size
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contour_detected_images[contour_directory+"/"+filename] = contour_detected_size
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current_path = os.getcwd()
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sftp.put_d(current_path+"/"+contour_directory,preserve_mtime=True,remotepath=remote_upload_path)
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contour_images = os.listdir(current_path+"/"+contour_directory)
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end = time1.time()
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exec_time = end-start
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decode_execution_time = params["exec_time_decode"]
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print(json.dumps({ "contour_images": contour_images,
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"image_contour_mappings": image_contour_mappings,
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"contour_detect_activation_id": str(activation_id),
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"number_of_images_processed": parts,
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"contour_execution_time": exec_time,
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"decode_execution_time": decode_execution_time,
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"contour_detected_images_size": contour_detected_images
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}))
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if __name__ == "__main__":
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main() |