Upload mask_the_face.py

mask_the_face.py

@@ -0,0 +1,132 @@
+# Author: aqeelanwar
+# Created: 27 April,2020, 10:22 PM
+# Email: aqeel.anwar@gatech.edu
+
+import argparse
+import dlib
+from aux_functions import *
+import numpy as np
+
+def maskThisImages(myImg):
+
+    # Command-line input setup
+    parser = argparse.ArgumentParser(
+        description="MaskTheFace - Python code to mask faces dataset"
+    )
+    parser.add_argument(
+        "--path",
+        type=str,
+        default="",
+        help="Path to either the folder containing images or the image itself",
+    )
+    parser.add_argument(
+        "--mask_type",
+        type=str,
+        default="surgical",
+        choices=["surgical", "N95", "KN95", "cloth", "gas", "inpaint", "random", "all"],
+        help="Type of the mask to be applied. Available options: all, surgical_blue, surgical_green, N95, cloth",
+    )
+
+    parser.add_argument(
+        "--pattern",
+        type=str,
+        default="",
+        help="Type of the pattern. Available options in masks/textures",
+    )
+
+    parser.add_argument(
+        "--pattern_weight",
+        type=float,
+        default=0.5,
+        help="Weight of the pattern. Must be between 0 and 1",
+    )
+
+    parser.add_argument(
+        "--color",
+        type=str,
+        default="cyan",
+        help="Hex color value that need to be overlayed to the mask",
+    )
+
+    parser.add_argument(
+        "--color_weight",
+        type=float,
+        default=0.5,
+        help="Weight of the color intensity. Must be between 0 and 1",
+    )
+
+    parser.add_argument(
+        "--code",
+        type=str,
+        # default="cloth-masks/textures/check/check_4.jpg, cloth-#e54294, cloth-#ff0000, cloth, cloth-masks/textures/others/heart_1.png, cloth-masks/textures/fruits/pineapple.png, N95, surgical_blue, surgical_green",
+        default="",
+        help="Generate specific formats",
+    )
+
+
+    parser.add_argument(
+        "--verbose", dest="verbose", action="store_true", help="Turn verbosity on"
+    )
+    parser.add_argument(
+        "--write_original_image",
+        dest="write_original_image",
+        action="store_true",
+        help="If true, original image is also stored in the masked folder",
+    )
+    parser.set_defaults(feature=False)
+
+    args, unknown = parser.parse_known_args()
+    args.write_path = args.path + "_masked"
+
+    # Set up dlib face detector and predictor
+    args.detector = dlib.get_frontal_face_detector()
+    path_to_dlib_model = "dlib_models/shape_predictor_68_face_landmarks.dat"
+    if not os.path.exists(path_to_dlib_model):
+        download_dlib_model()
+
+    args.predictor = dlib.shape_predictor(path_to_dlib_model)
+
+    # Extract data from code
+    mask_code = "".join(args.code.split()).split(",")
+    args.code_count = np.zeros(len(mask_code))
+    args.mask_dict_of_dict = {}
+
+
+    for i, entry in enumerate(mask_code):
+        print
+        mask_dict = {}
+        mask_color = ""
+        mask_texture = ""
+        mask_type = entry.split("-")[0]
+        if len(entry.split("-")) == 2:
+            mask_variation = entry.split("-")[1]
+            if "#" in mask_variation:
+                mask_color = mask_variation
+            else:
+                mask_texture = mask_variation
+        mask_dict["type"] = mask_type
+        mask_dict["color"] = mask_color
+        mask_dict["texture"] = mask_texture
+        args.mask_dict_of_dict[i] = mask_dict
+
+    # Check if path is file or directory or none
+    is_file=True
+    # Process if the path was a file
+    if is_file:
+        print("Masking image file")
+        image_path = args.path
+        write_path = args.path.rsplit(".")[0]
+        if True:
+            # Proceed if file is image
+            # masked_images, mask, mask_binary_array, original_image
+            masked_image, mask, mask_binary_array, original_image = mask_image(
+                myImg, args
+            )
+            if len(masked_image)==0:
+                return masked_image
+            else:
+                img = masked_image[i]
+                return img
+    else:
+        print("Path is neither a valid file or a valid directory")
+    print("Processing Done")