Add files to test footwear recognition

Author: GustavoDCC

image_recognition_footwear/test/assests/no_shoe.jpg

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+#!/usr/bin/env python
+
+import os
+import re
+from future.moves.urllib.request import urlretrieve
+import unittest
+
+from PIL import Image
+import rospkg
+from image_recognition_footwear.model import Model
+from image_recognition_footwear.process_data import heroPreprocess, detection_RGB
+import torch
+
+@unittest.skip
+def test_footwear():
+    local_path = "~/data/pytorch_models/footwearModel.pth"
+
+    if not os.path.exists(local_path):
+        print("File does not exit {}".format(local_path))
+
+    def is_there_footwear_from_asset_name(asset_name):
+        binary_str = re.search("(\w+)_shoe", asset_name).groups()
+        return binary_str == "yes"
+
+    assets_path = os.path.join(rospkg.RosPack().get_path("image_recognition_footwear"), 'test/assets')
+    images_gt = [(Image.open(os.path.join(assets_path, asset)), is_there_footwear_from_asset_name(asset))
+                 for asset in os.listdir(assets_path)]
+
+    device = torch.device('cuda')
+    model = Model(in_channel=3, channel_1=128, channel_2=256, channel_3=512, node_1=1024, node_2=1024, num_classes=2)
+    model.load_state_dict(torch.load(local_path))
+    model.to(device=device)
+    detections = detection_RGB([image for image, _ in images_gt], model)
+
+    estimations = AgeGenderEstimator(local_path, 64, 16, 8).estimate([image for image, _ in images_gt])
+
+    for (_, (is_footwear_gt)), (binary_detection) in zip(images_gt, detections):
+        binary_detection = int(binary_detection)
+        assert is_footwear_gt == binary_detection, f"{binary_detection=}, {is_footwear_gt=}"
+
+
+if __name__ == "__main__":
+    test_footwear()