--- a
+++ b/upload_images.py
@@ -0,0 +1,76 @@
+from gcloud import storage
+import argparse
+from enum import Enum
+import io
+from google.cloud import vision
+from google.cloud.vision import types
+from PIL import Image, ImageDraw
+import os
+import tempfile
+from pdf2image import convert_from_path, convert_from_bytes
+import pdf2image
+
+def convert_pdf(file_path, output_path=None):
+    print(file_path)
+    if ".JPG" in file_path:
+        jpg = Image.open(file_path)
+        jpg.save(output_path, 'JPEG', quality=80)
+        return jpg
+
+    if ".png" in file_path:
+        png = Image.open(file_path)
+        png.load() # required for png.split()
+
+        background = Image.new("RGB", png.size, (255, 255, 255))
+        background.paste(png, mask=png.split()[3]) # 3 is the alpha channel
+
+        background.save(output_path, 'JPEG', quality=80)
+        return background
+    # save temp image files in temp dir, delete them after we are finished
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # convert pdf to multiple image
+
+        images = convert_from_path(file_path, output_folder=temp_dir)
+
+        # save images to temporary directory
+        temp_images = []
+        for i in range(len(images)):
+            image_path = f'{temp_dir}/{i}.jpg'
+            images[i].save(image_path, 'JPEG')
+            temp_images.append(image_path)
+        # read images into pillow.Image
+        imgs = list(map(Image.open, temp_images))
+    # find minimum width of images
+    min_img_width = min(i.width for i in imgs)
+    # find total height of all images
+    total_height = 0
+    for i, img in enumerate(imgs):
+        total_height += imgs[i].height
+    # create new image object with width and total height
+    merged_image = Image.new(imgs[0].mode, (min_img_width, total_height))
+    # paste images together one by one
+    y = 0
+    for img in imgs:
+        merged_image.paste(img, (0, y))
+        y += img.height
+    # save merged image
+    merged_image.save(output_path, 'JPEG')
+    return merged_image
+
+
+if __name__ == '__main__':
+
+    # data_path = '/Users/rhettd/Documents/Fall2019/MED_CONSULT/Data/fwdfacesheets/'
+    data_path = '/Users/rhettd/Documents/Fall2019/MED_CONSULT/Data/CAA - CHICAGO ANESTHESIA ASSOCIATES SC/Single/'
+
+    client = storage.Client(project='medical-extraction')
+    bucket = client.get_bucket('report-ap')
+
+    for file_name in os.listdir(data_path):
+        if file_name != ".DS_Store" and file_name != "Done":
+            image_name = file_name.split('.')[0]
+
+            image = convert_pdf(data_path + file_name, data_path +"Done/"+ image_name + '.jpg')
+
+            blob = bucket.blob("face_sheet_images/" + image_name + '.jpg')
+            blob.upload_from_filename(data_path + "Done/"+ image_name+'.jpg')