crop/README.md

+The different files and directories contain the images and code necessary to construct the western corn rootworm (WCR) simulated dataset using the images given in the [Roboflow dataset](https://universe.roboflow.com/wcr-beetle-detection/wcr-beetle-traps). The content of each file is summarized below.
+
+- `beetles`: Directory of cropped WCR beetles taken from the cropped traps
+- `cropped_imgs`: Directory of cropped traps, containing both WCR beetles and insects
+- `imgs`: Directory of uncropped traps, containing both WCR beetles and insects
+- `non_beetles`: Directory of cropped various insects, not including WCR beetles, taken from the cropped traps
+- `SimData.ipynb`: Constructs the simulated dataset using the cropped traps, beetles, and insects in the various folders
+- `autocrop.py`: Performs cropping of an image using Otsu's Method, cropping only one image. To crop an image, setup the required environment and run the following command:
+```
+python3 autocrop.py imgpath destpath [sensitivity=110] [debug=False]
+```
+
+The available options are:
+```
+  imgpath               path to image file
+  destpath		path to destination file, including new filename
+  sensitivity		sensitivity of foreground vs background
+  debug		        saves additional images to folder (polygon and mask of foreground pixels)
+```
+*Note*: To perform autocropping, delete lines 111 and 133. These were implemented to be able to be used in `transfer.py`. 
+- `autocrop_folder.py`: Performs cropping of an image using Otsu's Method, cropping a whole folder. To crop a folder, setup the required environment and run the following command:
+```
+python3 autocrop_folder.py imgfolder destfolder [sensitivity=110] [debug=False]
+```
+The available options are:
+```
+  imgfolder             path to the folder of images
+  destfolder		path to destination folder
+  sensitivity		sensitivity of foreground vs background
+  debug		        saves additional images to folder (polygon and mask of foreground pixels)  
+```
+*Note*: When one file fails to autcrop due to needing a higher or lower sensitivity, the whole program stops. In this case, it is better to move it out of the folder and correctly crop it with a new sensitivity using `autocrop.py` and `debug=True`. Then, you can use `autocrop_folder.py` again.

crop/autocrop.py

+# https://stackoverflow.com/questions/60941012/how-do-i-find-corners-of-a-paper-when-there-are-printed-corners-lines-on-paper-i
+
+from PIL import Image
+import numpy as np
+import cv2
+import sys
+
+# does not work with heif rn
+def crop(img, sensitivity=110, debug=False):
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+    # Define lower and uppper limits of what we call "white-ish"
+    lower_white = np.array([0, 0, 255 - sensitivity])
+    upper_white = np.array([255, sensitivity, 255])
+
+    # Create mask to only select white
+    mask = cv2.inRange(hsv, lower_white, upper_white)
+
+    # Change image to green where we found white
+    nopole = img.copy()
+    nopole[mask > 0] = (76, 52, 40)
+
+    #  convert img to grayscale
+    gray = cv2.cvtColor(nopole, cv2.COLOR_BGR2GRAY)
+
+    # blur image
+    blur = cv2.GaussianBlur(gray, (3,3), 0)
+
+    # do otsu threshold on gray image
+    thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
+
+    # apply morphology
+    kernel = np.ones((7,7), np.uint8)
+    morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
+    morph = cv2.morphologyEx(morph, cv2.MORPH_OPEN, kernel)
+
+    # get largest contour
+    contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    contours = contours[0] if len(contours) == 2 else contours[1]
+    area_thresh = 0
+    for c in contours:
+        area = cv2.contourArea(c)
+        if area > area_thresh:
+            area_thresh = area
+            big_contour = c
+
+    # draw white filled largest contour on black just as a check to see it got the correct region
+    page = np.zeros_like(img)
+    cv2.drawContours(page, [big_contour], 0, (255,255,255), -1)
+
+    # get perimeter and approximate a polygon
+    peri = cv2.arcLength(big_contour, True)
+    corners = cv2.approxPolyDP(big_contour, 0.04 * peri, True)
+
+    # enforce CCW starting at top-left indexing
+    avgx = np.mean(corners[:,0,0])
+    avgy = np.mean(corners[:,0,1])
+
+    while(corners[0,0,0] > avgx or corners[0,0,1] > avgy):
+        corners = corners[[1,2,3,0], :, :]
+
+    # draw polygon on input image from detected corners
+    polygon = img.copy()
+    cv2.polylines(polygon, [corners], True, (0,0,255), 1, cv2.LINE_AA)
+    # Alternate: cv2.drawContours(page,[corners],0,(0,0,255),1)
+
+    # for simplicity get average of top/bottom side widths and average of left/right side heights
+    # note: probably better to get average of horizontal lengths and of vertical lengths
+    width = 0.5*( (corners[3][0][0] - corners[0][0][0]) + (corners[2][0][0] - corners[1][0][0]) )
+    height = 0.5*( (corners[1][0][1] - corners[0][0][1]) + (corners[2][0][1] - corners[3][0][1]) )
+    width = np.int0(width)
+    height = np.int0(height)
+
+    # reformat input corners to x,y list
+    icorners = []
+    for corner in corners:
+        pt = [ corner[0][0],corner[0][1] ]
+        icorners.append(pt)
+    icorners = np.float32(icorners)
+
+    # get corresponding output corners from width and height
+    ocorners = [ [0,0], [0,height], [width,height], [width,0] ]
+    ocorners = np.float32(ocorners)
+
+    # get perspective tranformation matrix
+    M = cv2.getPerspectiveTransform(icorners, ocorners)
+
+    # do perspective 
+    warped = cv2.warpPerspective(img, M, (width, height))
+    
+    warped_rgb = cv2.cvtColor(warped, cv2.COLOR_BGR2RGB)
+    polygon_rgb = cv2.cvtColor(polygon, cv2.COLOR_BGR2RGB)
+    
+    if not debug:
+        return warped_rgb
+    return warped_rgb, page, polygon_rgb
+
+def cropFromFile(imgpath, destpath, sensitivity=110, debug=False):
+    img = cv2.imread(imgpath)
+    ret = crop(img, sensitivity, debug)
+
+    if not debug:
+        warped_rgb = ret
+    else:
+        warped_rgb, page, polygon_rgb = ret
+        Image.fromarray(page).save(destpath+"page.jpg")
+        Image.fromarray(polygon_rgb).save(destpath+"polygon.jpg")
+    
+    Image.fromarray(warped_rgb).save(destpath)
+
+'''
+if len(sys.argv) < 3 or len(sys.argv) > 5 :
+    sys.print("Format: python3 autocrop.py imgpath destpath [sensitivity=110] [debug=False]")
+    exit(1)
+
+if len(sys.argv) == 3:
+    cropFromFile(sys.argv[1], sys.argv[2])
+
+elif len(sys.argv) == 5:
+    if sys.argv[4] == "True":
+        cropFromFile(sys.argv[1], sys.argv[2], int(sys.argv[3]), True)
+    else:
+        cropFromFile(sys.argv[1], sys.argv[2], int(sys.argv[3]), False)
+
+else:
+    try:
+        cropFromFile(sys.argv[1], sys.argv[2], sensitivity=int(sys.argv[3]))
+    except ValueError:
+        if sys.argv[3] == "True":
+            cropFromFile(sys.argv[1], sys.argv[2], debug=True)
+        else:
+            cropFromFile(sys.argv[1], sys.argv[2], debug=False)
+'''
\ No newline at end of file