Image Classifier Using SDK - Uploading and Training the Model

base_image_location = "CourseAssets/ImageClassification/Images"
print("Adding images...")
image_list = []
for image_num in range(1, 11):
    file_name = "hemlock_{}.jpg".format(image_num)
    with open(base_image_location + "/Hemlock/" + file_name, "rb") as hemlock_image:
        image_list.append(
                ImageFileCreateEntry(
                    name = file_name, 
                    contents = hemlock_image.read(), 
                    tag_ids= [hemlock_tag.id]
                )
            )
for image_num in range(1, 11):
    file_name = "japanese_cherry_{}.jpg".format(image_num)
    with open(base_image_location + "/Japanese_Cherry/" + file_name, "rb") as cherry_image:
        image_list.append(
                ImageFileCreateEntry(
                    name = file_name, 
                    contents = cherry_image.read(), 
                    tag_ids = [cherry_tag.id]
                )
            )
upload_result = trainer.create_images_from_files(
                        project.id, 
                        ImageFileCreateBatch(images = image_list)
                    )
if not upload_result.is_batch_successful:
    print("Image batch upload failed.")
    for image in upload_result.images:
        print("Image status: ", image.status)
else:
    print("Imaged Added Successfully!!")