Merge pull request #2 from apoorva-mk/Computer_Vision

Computer vision

Data_Collection/images.json

@@ -0,0 +1,109 @@
+{
+    "Records": [
+	{
+            "keywords": "washing machine"
+        },
+        {
+            "keywords": "telephone"
+        },
+        {
+            "keywords": "sewing machine"
+        },
+        {
+            "keywords": "radio"
+        },
+        {
+            "keywords": "stereo"
+        },
+        {
+            "keywords": "sofa"
+        },
+        {
+            "keywords": "ceiling fan"
+        },
+        {
+            "keywords": "table fan"
+        },
+        {
+            "keywords": "armchair"
+        },
+        {
+            "keywords": "cattle"
+        },
+        {
+            "keywords": "mattress"
+        },
+        {
+            "keywords": "chair"
+        },
+        {
+            "keywords": "tube light"
+        },
+        {
+            "keywords": "bulb light"
+        },
+        {
+            "keywords": "gas cylinder"
+        },
+        {
+            "keywords": "stove"
+        },
+        {
+            "keywords": "electric iron"
+        },
+        {
+            "keywords": "kitchen sink"
+        },
+        {
+            "keywords": "desktop computer"
+        },
+        {
+            "keywords": "food mixer"
+        },
+        {
+            "keywords": "food processor"
+        },
+        {
+            "keywords": "pressure cooker"
+        },
+        {
+            "keywords": "cars"
+        },
+        {
+            "keywords": "bicycles"
+        },
+        {
+            "keywords": "motorcycles"
+        },
+        {
+            "keywords": "vacuum cleaner"
+        },
+        {
+            "keywords": "thermos flask"
+        },
+        {
+            "keywords": "dish antenna"
+        },
+        {
+            "keywords": "firewood"
+        },
+        {
+            "keywords": "brick wall"
+        },
+        {
+            "keywords": "stone wall"
+        },
+        {
+            "keywords": "mud walls"
+        },
+        {
+            "keywords": "wardrobe"
+        },
+        {
+            "keywords": "oven"
+        },
+        {
+            "keywords": "microwave oven"
+        }
+    ]
+}

Data_Collection/xml_to_csv.py

@@ -0,0 +1,38 @@
+import os
+import glob
+import pandas as pd
+import xml.etree.ElementTree as ET
+
+def xml_to_csv(path):
+    xml_list = []
+    for xml_file in glob.glob(path + '/*.xml'):
+        tree = ET.parse(xml_file)
+        root = tree.getroot()
+        for member in root.findall('object'):
+            value = (
+            		 "UNASSIGNED",
+            		 root.find('filename').text,
+                     member[0].text,
+                     int(member[4][0].text)/int(root.find('size')[0].text),
+                     int(member[4][1].text)/int(root.find('size')[1].text),
+                     None,
+                     None,
+                     int(member[4][2].text)/int(root.find('size')[0].text),
+                     int(member[4][3].text)/int(root.find('size')[1].text),
+                     None,
+                     None
+                     )
+            xml_list.append(value)
+    #column_name = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
+    column_name = ['','filename','class','xmin', 'ymin','','','xmax', 'ymax','','']
+    xml_df = pd.DataFrame(xml_list, columns=column_name)
+    return xml_df
+
+def main():
+    image_path = os.path.join(os.getcwd(), 'annotations')
+    xml_df = xml_to_csv(image_path)
+    xml_df.to_csv('raccoon_labels.csv', index=None)
+    print('Successfully converted xml to csv.')
+
+
+main()