diff --git a/README.md b/README.md
index 1ea16cb93..8f62f6941 100644
--- a/README.md
+++ b/README.md
@@ -405,6 +405,7 @@ If you would like to try on your computer:
| [
](image_inpainting/inpainting_gmcnn/) | [inpainting_gmcnn](/image_inpainting/inpainting_gmcnn/) | [Image Inpainting via Generative Multi-column Convolutional Neural Networks](https://github.com/shepnerd/inpainting_gmcnn) | TensorFlow | 1.2.6 and later |
| [
](image_inpainting/3d-photo-inpainting/) | [3d-photo-inpainting](/image_inpainting/3d-photo-inpainting/) | [3D Photography using Context-aware Layered Depth Inpainting](https://github.com/vt-vl-lab/3d-photo-inpainting) | Pytorch | 1.2.7 and later |
| [
](image_inpainting/deepfillv2/) | [deepfillv2](/image_inpainting/deepfillv2/) | [Free-Form Image Inpainting with Gated Convolution](https://github.com/open-mmlab/mmediting/tree/master/configs/inpainting/deepfillv2) | Pytorch | 1.2.9 and later |
+[
](image_inpainting/lama/) | [lama](/image_inpainting/lama/) | [LaMa: Resolution-robust Large Mask Inpainting with Fourier Convolutions](https://github.com/advimman/lama) | Pytorch | 2.0.0 and later |
## Image manipulation
diff --git a/image_inpainting/lama/000068.png b/image_inpainting/lama/000068.png
new file mode 100644
index 000000000..6f74ce42f
Binary files /dev/null and b/image_inpainting/lama/000068.png differ
diff --git a/image_inpainting/lama/000068_mask.png b/image_inpainting/lama/000068_mask.png
new file mode 100644
index 000000000..a1efb8a0f
Binary files /dev/null and b/image_inpainting/lama/000068_mask.png differ
diff --git a/image_inpainting/lama/LICENSE b/image_inpainting/lama/LICENSE
new file mode 100644
index 000000000..ca822bb5f
--- /dev/null
+++ b/image_inpainting/lama/LICENSE
@@ -0,0 +1,201 @@
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diff --git a/image_inpainting/lama/README.md b/image_inpainting/lama/README.md
new file mode 100644
index 000000000..76480a76d
--- /dev/null
+++ b/image_inpainting/lama/README.md
@@ -0,0 +1,51 @@
+# LaMa: Resolution-robust Large Mask Inpainting with Fourier Convolutions
+
+## Input
+
+
+
+
+
+(Image from https://drive.google.com/drive/folders/1B2x7eQDgecTL0oh3LSIBDGj0fTxs6Ips?usp=drive_link)
+
+Shape : (1, 3, 1499, 996)
+
+## Output
+
+
+
+Shape : (1, 1, 1499, 996)
+
+## Usage
+
+Automatically downloads the onnx and prototxt files on the first run.
+It is necessary to be connected to the Internet while downloading.
+
+For the sample image,
+
+```bash
+$ python3 lama.py
+```
+If you want to specify both the input image and a mask, provide their paths using the --input and --mask options.
+You can use `--savepath` option to change the name of the output file to save.
+
+```bash
+$ python3 lama.py --input IMAGE_PATH --mask MASK_PATH --savepath SAVE_IMAGE_PATH
+```
+
+
+## Reference
+
+[LaMa: Resolution-robust Large Mask Inpainting with Fourier Convolutions](https://github.com/advimman/lama)
+
+## Framework
+
+Pytorch
+
+## Model Format
+
+ONNX opset=17
+
+## Netron
+
+[lama.onnx.prototxt](https://netron.app/?url=https://storage.googleapis.com/ailia-models/lama/lama.onnx.prototxt)
diff --git a/image_inpainting/lama/lama.py b/image_inpainting/lama/lama.py
new file mode 100644
index 000000000..9801dd5d4
--- /dev/null
+++ b/image_inpainting/lama/lama.py
@@ -0,0 +1,134 @@
+import sys
+import time
+import os
+import platform
+
+import cv2
+import numpy as np
+
+import ailia
+
+# import original modules
+sys.path.append('../../util')
+from arg_utils import get_base_parser, update_parser, get_savepath # noqa: E402
+from model_utils import check_and_download_models # noqa: E402
+from image_utils import imread # noqa: E402
+
+# logger
+from logging import getLogger # noqa: E402
+
+logger = getLogger(__name__)
+
+# ======================
+# Parameters
+# ======================
+WEIGHT_PATH = 'lama.onnx'
+MODEL_PATH = 'lama.onnx.prototxt'
+
+REMOTE_PATH = 'https://storage.googleapis.com/ailia-models/lama/'
+
+IMAGE_PATH = '000068.png'
+MASK_PATH = '000068_mask.png'
+SAVE_IMAGE_PATH = 'output.png'
+
+# ======================
+# Arguemnt Parser Config
+# ======================
+parser = get_base_parser('Lama model', IMAGE_PATH, SAVE_IMAGE_PATH)
+parser.add_argument(
+ '-m', '--mask', nargs='*', metavar='MASK_PATH', default=[MASK_PATH],
+ help='using mask image from mask path'
+)
+args = update_parser(parser)
+
+
+# ======================
+# Main functions
+# ======================
+
+def ceil_modulo(x, mod):
+ if x % mod == 0:
+ return x
+ return (x // mod + 1) * mod
+
+
+def pad_img_to_modulo(img, mod):
+ channels, height, width = img.shape
+ out_height = ceil_modulo(height, mod)
+ out_width = ceil_modulo(width, mod)
+ return np.pad(img, ((0, 0), (0, out_height - height), (0, out_width - width)), mode='symmetric')
+
+
+def preprocess(image):
+ pad_out_to_modulo = 8
+ image = pad_img_to_modulo(image, pad_out_to_modulo)
+ return image
+
+
+def recognize_from_image(net):
+ # input image loop
+ for image_path , mask_path in zip(args.input,args.mask):
+ # prepare ground truth
+ image = imread(image_path).astype(np.float32)/255
+ image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+ image = np.transpose(image, (2, 0, 1))
+ image = preprocess(image).astype(np.float32)
+
+ # prepare mask
+ mask = imread(mask_path ,cv2.IMREAD_GRAYSCALE)[None, ...] / 255
+ mask = preprocess(mask).astype(np.float32)
+ mask = (mask > 0) * 1
+
+ # prepare input data
+ logger.debug(f'input data shape: {image.shape}')
+
+ # inference
+ logger.info('Start inference...')
+ if args.benchmark:
+ logger.info('BENCHMARK mode')
+ total_time = 0
+ for i in range(args.benchmark_count):
+ start = int(round(time.time() * 1000))
+
+ results = net.run((np.expand_dims(image,0),
+ np.expand_dims(mask ,0)))
+
+ end = int(round(time.time() * 1000))
+ logger.info(f'\tailia processing time {end - start} ms')
+ if i != 0:
+ total_time = total_time + (end - start)
+ logger.info(f'\taverage time {total_time / (args.benchmark_count - 1)} ms')
+ else:
+ results = net.run((np.expand_dims(image,0),
+ np.expand_dims(mask ,0)))
+
+ savepath = get_savepath(args.savepath, image_path, ext='.png')
+ logger.info(f'saved at : {savepath}')
+
+ results = np.array(results[0][0])
+ results = np.transpose(results,(1,2,0)).astype("uint8")
+
+ res_img = cv2.cvtColor(results, cv2.COLOR_RGB2BGR)
+
+ cv2.imwrite(savepath, res_img)
+
+ logger.info('Script finished successfully.')
+
+def main():
+
+ if "FP16" in ailia.get_environment(args.env_id).props or platform.system() == 'Darwin':
+ logger.warning('This model do not work on FP16. So use CPU mode.')
+ args.env_id = 0
+
+ # model files check and download
+ check_and_download_models(MODEL_PATH, MODEL_PATH, REMOTE_PATH)
+
+ memory_mode = ailia.get_memory_mode(reduce_constant=True, reduce_interstage=True)
+ # net initialize
+ net = ailia.Net(MODEL_PATH, WEIGHT_PATH,memory_mode=memory_mode, env_id=args.env_id)
+
+ recognize_from_image(net)
+
+
+if __name__ == '__main__':
+ main()
diff --git a/scripts/download_all_models.sh b/scripts/download_all_models.sh
index cd277ac26..08899bab4 100755
--- a/scripts/download_all_models.sh
+++ b/scripts/download_all_models.sh
@@ -169,6 +169,7 @@ cd ../../image_inpainting/3d-photo-inpainting; python3 3d-photo-inpainting.py ${
cd ../../image_inpainting/inpainting_gmcnn; python3 inpainting_gmcnn.py ${OPTION}
cd ../../image_inpainting/pytorch-inpainting-with-partial-conv; python3 pytorch-inpainting-with-partial-conv.py ${OPTION}
cd ../../image_inpainting/deepfillv2; python3 deepfillv2.py ${OPTION}
+cd ../../image_inpainting/lama; python3 lama.py ${OPTION}
cd ../../image_manipulation/dewarpnet; python3 dewarpnet.py ${OPTION}
cd ../../image_manipulation/illnet; python3 illnet.py ${OPTION}
cd ../../image_manipulation/noise2noise; python3 noise2noise.py ${OPTION}