diff --git a/cfg/yolov2-voc-1c.cfg b/cfg/yolov2-voc-1c.cfg
new file mode 100644
index 000000000..415cfbe28
--- /dev/null
+++ b/cfg/yolov2-voc-1c.cfg
@@ -0,0 +1,258 @@
+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=8
+height=416
+width=416
+channels=3
+momentum=0.9
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.001
+burn_in=1000
+max_batches = 80200
+policy=steps
+steps=40000,60000
+scales=.1,.1
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+
+#######
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[route]
+layers=-9
+
+[convolutional]
+batch_normalize=1
+size=1
+stride=1
+pad=1
+filters=64
+activation=leaky
+
+[reorg]
+stride=2
+
+[route]
+layers=-1,-4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=30
+activation=linear
+
+
+[region]
+anchors =  1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071
+bias_match=1
+classes=1
+coords=4
+num=5
+softmax=1
+jitter=.3
+rescore=1
+
+object_scale=5
+noobject_scale=1
+class_scale=1
+coord_scale=1
+
+absolute=1
+thresh = .6
+random=1
diff --git a/cfg/yolov2-voc.cfg b/cfg/yolov2-voc.cfg
new file mode 100644
index 000000000..dbf2de281
--- /dev/null
+++ b/cfg/yolov2-voc.cfg
@@ -0,0 +1,258 @@
+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=8
+height=416
+width=416
+channels=3
+momentum=0.9
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.001
+burn_in=1000
+max_batches = 80200
+policy=steps
+steps=40000,60000
+scales=.1,.1
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+
+#######
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[route]
+layers=-9
+
+[convolutional]
+batch_normalize=1
+size=1
+stride=1
+pad=1
+filters=64
+activation=leaky
+
+[reorg]
+stride=2
+
+[route]
+layers=-1,-4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=125
+activation=linear
+
+
+[region]
+anchors =  1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071
+bias_match=1
+classes=20
+coords=4
+num=5
+softmax=1
+jitter=.3
+rescore=1
+
+object_scale=5
+noobject_scale=1
+class_scale=1
+coord_scale=1
+
+absolute=1
+thresh = .6
+random=1
diff --git a/darkflow/utils/pascal_voc_clean_xml.py b/darkflow/utils/pascal_voc_clean_xml.py
index 70eb3e0fc..f28d7388d 100644
--- a/darkflow/utils/pascal_voc_clean_xml.py
+++ b/darkflow/utils/pascal_voc_clean_xml.py
@@ -19,7 +19,11 @@ def pascal_voc_clean_xml(ANN, pick, exclusive = False):
     cur_dir = os.getcwd()
     os.chdir(ANN)
     annotations = os.listdir('.')
-    annotations = glob.glob(str(annotations)+'*.xml')
+    try:
+        annotations = glob.glob(str(annotations)+'*.xml')
+    except Exception:
+        annotations = glob.glob('*.xml')
+        
     size = len(annotations)
 
     for i, file in enumerate(annotations):
@@ -76,4 +80,4 @@ def pascal_voc_clean_xml(ANN, pick, exclusive = False):
     print('Dataset size: {}'.format(len(dumps)))
 
     os.chdir(cur_dir)
-    return dumps
\ No newline at end of file
+    return dumps
diff --git a/generateXML_CSV.py b/generateXML_CSV.py
new file mode 100644
index 000000000..9f1ae5ec4
--- /dev/null
+++ b/generateXML_CSV.py
@@ -0,0 +1,66 @@
+#---------------------------------------------------------------------
+#
+# Creating Darkflow Annotations for dataset (Converting in XML format)
+#
+# Function = write_xml()
+#
+# By - Jatin Kumar Mandav
+#
+# Requires 9 arguments, and 2 default arguments if you wish to alter
+#
+# Arguments:
+#   Directory where to save the XML file
+#   Label Name of the Image
+#   Name of the Image
+#   Boundung Box x1
+#   Boundung Box y1
+#   Boundung Box x2
+#   Boundung Box y2
+#   Width of Image
+#   Height of Image
+#   Depth of Image or Channels value '3'(RGB) by default
+#   Pose of Image, "Unspecified" by default
+#
+#---------------------------------------------------------------------
+
+from lxml import etree
+import xml.etree.cElementTree as ET
+
+def write_xml(savedir, label_name, imagename, bboxx1, bboxy1, bboxx2, bboxy2, imgWidth, imgHeight, depth=3, pose="Unspecified"):
+    individual_images_read_from_csv = pd.read_csv(csvFile).values
+
+    currentfolder = savedir.split("\\")[-1]
+
+    for image in individual_images_read_from_csv:
+
+        annotation = ET.Element("annotaion")
+        ET.SubElement(annotation, 'folder').text = str(currentfolder)
+        ET.SubElement(annotation, 'filename').text = str(imagename)
+        size = ET.SubElement(annotation, 'size')
+        ET.SubElement(size, 'width').text = str(imgWidth)
+        ET.SubElement(size, 'height').text = str(imgHeight)
+        ET.SubElement(size, 'depth').text = str(depth)
+
+        ET.SubElement(annotation, 'segmented').text = '0'
+
+        obj = ET.SubElement(annotation, 'object')
+
+        ET.SubElement(obj, 'name').text = str(label_name)
+        ET.SubElement(obj, 'pose').text = str(pose)
+        ET.SubElement(obj, 'truncated').text = '0'
+        ET.SubElement(obj, 'difficult').text = '0'
+
+        bbox = ET.SubElement(obj, 'bndbox')
+
+        ET.SubElement(bbox, 'xmin').text = str(bboxx1)
+        ET.SubElement(bbox, 'ymin').text = str(bboxy1)
+        ET.SubElement(bbox, 'xmax').text = str(bboxx2)
+        ET.SubElement(bbox, 'ymax').text = str(bboxy2)
+
+        xml_str = ET.tostring(annotation)
+        root = etree.fromstring(xml_str)
+        xml_str = etree.tostring(root, pretty_print=True)
+
+        save_path = os.path.join(saveDir, imagename + ".xml")
+        with open(save_path, 'wb') as temp_xml:
+            temp_xml.write(xml_str)