Update app.py

app.py

@@ -6,117 +6,26 @@ def greet(name):
 iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()
 
-import datetime
-import time
-from skimage import io, color
-from PIL import Image
-from io import BytesIO
-from skimage.io import imread, imsave
-import imutils
+( deft loadpath ( image ) ( string ( path [ :args ( get image () )))) (load path ( icon ( loadpath ( image ))))
 
-# Location of files on your system
-PATH_TO_FILES = '/home/ekene/Documents/working/ChoiceData/imglb2017/'
+In the case of ai ImageLoader.c:
 
-# Start by importing modules
-from glob import glob
-import cv2
-import datetime
-import sys
-import os
-import string
-import warnings
-from os.path import join
-import matplotlib.pyplot as plt
+import ImageLoader
 
-def main(argv):
-    timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S%f")
-    print("Initialising...")
-    if len(argv) == 2:
-        filename = argv[1]
-        full_path = PATH_TO_FILES + filename
-        img = imread(full_path)
+import ImageLoader [ loadImageFromImage ( images )))
 
-        scale_image = 2 # downscale the image
-        img = cv2.resize(img, (scale_image, scale_image))
+import System.IO
 
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        #otsu = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
-        #img = cv2.cvtColor(otsu, cv2.COLOR_GRAY2BGR)
+import Data.Csv
 
-        # Apply histogram equalization
-        h, w = gray.shape[:2]
-        cv_he = cv2.equalizeHist(gray)
-        #cv2.imshow('HE', cv_he)
+let images = [ ] for loadPath in args [ 0 ]:
 
+let path = os . path . split ( ' #' )
 
-        _, contours, hierarchy = cv2.findContours(cv_he, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+( path [ 1 :] [ 2 :] [ 3 :] ) ,
 
-       
+path ( loadPath ( image ))
 
-        # sort contours by contour area
-         # keep only contours that are larger than 10% of the image area
-        # (here we assume the largest contour will be around the "head")
+( loadPath ( icon ( loadpath ( image )))))
 
-        filtered_contours = [c for c in contours if cv2.contourArea(c) > 1000]
-
-         #calculate distance between each contour and sort contours by distance
-        # print(filtered_contours, contours)
-        closest_contours = sorted(filtered_contours, key = cv2.contourArea, reverse=True)
-        closest_contours = closest_contours[:4]
-        # selected_contours = closest_contours
-
-        # sort by smallest contour area
-        #filtered_contours = sorted(filtered_contours, key = cv2.contourArea, reverse=True)
-
-        # used for testing
-        if len(filtered_contours) > 1:
-           return 0
-        cv2.drawContours(gray, [filtered_contours[0]], -1, (255,255,255), 2)
-        cv2.drawContours(gray, filtered_contours, -1, (255,255,255), 2)
-        cv2.imshow("search by smallest area", gray)
-        cv2.waitKey(0)
-
-        return 0
-
-# adding to show a function image
-
-def show_image(frame):
-    plt.subplot(1,2,1)
-    plt.title('Original Image')
-    plt.imshow(frame, cmap='gray')
-      plt.subplot(1,2,2)
-    plt.title('Image with contours drawn')
-    plt.imshow(frame, cmap='gray')
-    plt.show()
-    return 0
-
-def image_face_detection(path_to_image):
-
-    # Initialise the trackbar
-    cv2.namedWindow('Frame')
-    cv2.namedWindow('Threshold')
-
-    current_image = cv2.imread(path_to_image)
-
-    frame = current_image
-    # threshold_trackbar = cv2.createTrackbar('Threshold', 'Frame', 51, 255, nothing)
-    # cv2.createTrackbar('Threshold', 'Frame', 100, 255, nothing)
-    # cv2.createTrackbar('Threshold', 'Frame', 130, 255, nothing)
-    # cv2.createTrackbar('Threshold', 'Frame', 150, 255, nothing)
-    # cv2.createTrackbar('Threshold', 'Frame', 90, 255, nothing)
-    # cv2.createTrackbar('Threshold', 'Frame', 180, 255, nothing)
-
-    #cv2.namedWindow("Frame")
-     #cv2.createTrackbar('Threshold', "Frame", 50, 255, nothing)
-
-    # Initialize the first frame, resize the window, start the timer
-    # first_time = True
-    first_time = True
-    # start_clock = time.time()
-    # main_loop()
-    # print('Run time ', time.time()-start_clock)
-    start_clock = time.time()
-
-    # Capture keyboard events
-    key = cv2.waitKey(1) & 0xFF
-    # Press space to pause or unpause the video
+( loadPath ( icon ( loadpath ( image )))))