Update darknet.py, OpenCV.py, removeBackground.py files

OpenCV.py

+import cv2
+
+from utils import *
+from darknet import Darknet
+from flask import Flask
+from flask import request
+
+app = Flask(__name__)
+
+cfg_file = 'cfg/yolov3.cfg'
+weight_file = 'weights/yolov3.weights'
+namesfile = 'data/coco.names'
+
+m = Darknet(cfg_file)
+
+m.load_weights(weight_file)
+
+class_names = load_class_names(namesfile)
+
+plt.rcParams['figure.figsize'] = [24.0, 14.0]
+
+@app.route("/OpenCV")
+def hello():
+    filePath = request.args.get('file')
+
+    img = cv2.imread(filePath)
+
+    original_image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+
+    resized_image = cv2.resize(original_image, (m.width, m.height))
+
+    iou_thresh = 0.4
+
+    nms_thresh = 0.6
+    boxes = detect_objects(m, resized_image, iou_thresh, nms_thresh)
+
+    return print_objects(boxes, class_names)
+
+if __name__ == '__main__':
+    app.run(debug=True, port=5000)
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removeBackground.py

+import cv2
+import numpy as np
+
+#== Parameters =======================================================================
+BLUR = 21
+CANNY_THRESH_1 = 0
+CANNY_THRESH_2 = 50
+MASK_DILATE_ITER = 10
+MASK_ERODE_ITER = 10
+MASK_COLOR = (1.0,1.0,1.0) # In BGR format
+
+
+#== Processing =======================================================================
+
+#-- Read image -----------------------------------------------------------------------
+img = cv2.imread('test.jpeg')
+gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+
+#-- Edge detection -------------------------------------------------------------------
+edges = cv2.Canny(gray, CANNY_THRESH_1, CANNY_THRESH_2)
+edges = cv2.dilate(edges, None)
+edges = cv2.erode(edges, None)
+
+#-- Find contours in edges, sort by area ---------------------------------------------
+contour_info = []
+# _, contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
+# Previously, for a previous version of cv2, this line was:
+contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
+# Thanks to notes from commenters, I've updated the code but left this note
+for c in contours:
+    contour_info.append((
+        c,
+        cv2.isContourConvex(c),
+        cv2.contourArea(c),
+    ))
+contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True)
+max_contour = contour_info[0]
+
+#-- Create empty mask, draw filled polygon on it corresponding to largest contour ----
+# Mask is black, polygon is white
+mask = np.zeros(edges.shape)
+cv2.fillConvexPoly(mask, max_contour[0], (255))
+
+#-- Smooth mask, then blur it --------------------------------------------------------
+mask = cv2.dilate(mask, None, iterations=MASK_DILATE_ITER)
+mask = cv2.erode(mask, None, iterations=MASK_ERODE_ITER)
+mask = cv2.GaussianBlur(mask, (BLUR, BLUR), 0)
+mask_stack = np.dstack([mask]*3)    # Create 3-channel alpha mask
+
+#-- Blend masked img into MASK_COLOR background --------------------------------------
+mask_stack  = mask_stack.astype('float32') / 255.0          # Use float matrices,
+img         = img.astype('float32') / 255.0                 #  for easy blending
+
+masked = (mask_stack * img) + ((1-mask_stack) * MASK_COLOR) # Blend
+masked = (masked * 255).astype('uint8')                     # Convert back to 8-bit
+
+cv2.imshow('img', masked)                                   # Display
+cv2.waitKey()
+
+#cv2.imwrite('C:/Temp/person-masked.jpg', masked)           # Save
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