Batch Crop Image (Mikey)

Documentation

• Class name: Batch Crop Image
• Category: Mikey/Image
• Output node: False

The BatchCropImage node is designed for processing a batch of images by cropping them based on a specified amount. It operates on a directory of images, applying a uniform crop operation to each image to reduce their dimensions by a certain percentage, thereby preparing the images for further processing or analysis.

Input types

Required

• image_directory
  • Specifies the directory containing the images to be processed. It is crucial for locating and accessing the batch of images for cropping.
  • Comfy dtype: STRING
  • Python dtype: str
• crop_amount
  • Determines the percentage of the image to be cropped from each side. This parameter directly influences the final size of the cropped images, affecting both their width and height.
  • Comfy dtype: FLOAT
  • Python dtype: float

Output types

• image
  • Comfy dtype: IMAGE
  • The cropped images are returned as a list, with each element representing a cropped version of the original images found in the specified directory.
  • Python dtype: List[torch.Tensor]

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class BatchCropImage:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"image_directory": ("STRING", {"multiline": False, "placeholder": "Image Directory"}),
                             "crop_amount": ("FLOAT", {"default": 0.05})}}

    RETURN_TYPES = ('IMAGE',)
    RETURN_NAMES = ('image',)
    FUNCTION = 'batch'
    CATEGORY = 'Mikey/Image'
    OUTPUT_IS_LIST = (True, )

    def batch(self, image_directory, crop_amount):
        if not os.path.exists(image_directory):
            raise Exception(f"Image directory {image_directory} does not exist")

        images = []
        for file in os.listdir(image_directory):
            if file.endswith('.png') or file.endswith('.jpg') or file.endswith('.jpeg') or file.endswith('.webp') or file.endswith('.bmp') or file.endswith('.gif'):
                img = Image.open(os.path.join(image_directory, file))
                # resize image
                width, height = img.size
                pixels = int(width * crop_amount) // 8 * 8
                left = pixels
                upper = pixels
                right = width - pixels
                lower = height - pixels
                # Crop the image
                cropped_img = img.crop((left, upper, right, lower))
                img = pil2tensor(cropped_img)
                images.append(img)
        return (images,)