Fork of Lornatang/ESPCN-PyTorch

Differences between original repository and fork:

• Compatibility with PyTorch >=2.4. (🔥)
• Original pretrained models and converted ONNX models from GitHub releases page. (🔥)
• Model conversion to ONNX format using the export.py file. (🔥)
• Installation with updated requirements.txt file.
• The following deprecations has been fixed:
  • FutureWarning: You are using 'torch.load' with 'weights_only=False'.

Installation

shell pip install -r requirements.txt

Pretrained models

• Download links:

| Name | Model Size (MB) | Link | SHA-256 | |----------|-----------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------| | ESPCNx2 | 0.1
0.1 | PyTorch, ONNX | 67321a870da341c15a92f5dcea31bcb21b7fa30165b0ac445662d4364048595b
6c806349be7f963f3d0895050a771a5de15e9950361e2a2f92624e4b1f675044 | | ESPCNx3 | 0.1
0.1 | PyTorch, ONNX | 242ab640f79fa1e005f5d495debf6c1e385209c8b81f14f5692ba7ed51ec2f5d
77aea5de0ba9628566ef9519de06a18ff5c25b32b0743d3e49a808c539c5445f | | ESPCN_x4 | 0.1
0.1 | PyTorch, ONNX | 756564c1b4103cad1170479bbce665b2b58163444d5170dcc1db37ba143694f8
2b421d032afd5737c8cc0f1145214d78c35dbc46e3c7cb45913da80304b8aa8e |

• Evaluation results:

| Name | Scale | Set5 (PSNR) | Set14 (PSNR) | |----------|-------|-------------|--------------| | ESPCNx2 | 2 | 36.64 | 32.35 | | ESPCNx3 | 3 | 32.55 | 29.20 | | ESPCN_x4 | 4 | 30.26 | 27.41 |

Inference

shell python inference.py --model_arch_name espcn_x2 --upscale_factor 2 --model_weights_path espcn-x2.pth.tar --inputs_path figure/comic.png --output_path figure/sr_comic_x2.png python inference.py --model_arch_name espcn_x3 --upscale_factor 3 --model_weights_path espcn-x3.pth.tar --inputs_path figure/comic.png --output_path figure/sr_comic_x3.png python inference.py --model_arch_name espcn_x4 --upscale_factor 4 --model_weights_path espcn-x4.pth.tar --inputs_path figure/comic.png --output_path figure/sr_comic_x4.png

Export to ONNX format

shell pip install onnx shell python export.py --model_arch_name espcn_x2 --model_weights_path espcn-x2.pth.tar python export.py --model_arch_name espcn_x3 --model_weights_path espcn-x3.pth.tar python export.py --model_arch_name espcn_x4 --model_weights_path espcn-x4.pth.tar