Add: Add better FID calculator to verify image quality.

README.md

@@ -85,6 +85,7 @@ Integrated Design Diffusion Model
 ├── tools
 │   ├── deploy.py
 │   ├── FID_calculator.py
+│   ├── FID_calculator_plus.py
 │   ├── generate.py
 │   └── train.py
 ├── utils
@@ -114,6 +115,7 @@ Integrated Design Diffusion Model
 - [x] 10. Reconstruct the overall structure of the model (2023-12-06)
 - [x] 11. Write visual webui interface. (2024-01-23)
 - [x] 12. Adding PLMS Sampling Method. (2024-03-12)
+- [x] 13. Adding FID calculator to verify image quality. (2024-05-06)
 
 ### Training
 

README_zh.md

@@ -84,6 +84,7 @@ Integrated Design Diffusion Model
 ├── tools
 │   ├── deploy.py
 │   ├── FID_calculator.py
+│   ├── FID_calculator_plus.py
 │   ├── generate.py
 │   └── train.py
 ├── utils
@@ -113,6 +114,7 @@ Integrated Design Diffusion Model
 - [x] 10. 重构model整体结构（2023-12-06）
 - [x] 11. 编写可视化webui界面（2024-01-23）
 - [x] 12. 增加PLMS采样方法（2024-03-12）
+- [x] 13. 增加FID方法验证图像质量（2024-05-06）
 
 ### 训练
 

tools/FID_calculator_plus.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+"""
+    @Date   : 2024/5/4 23:36
+    @Author : chairc
+    @Site   : https://github.com/chairc
+"""
+import os
+import sys
+import argparse
+import logging
+
+import coloredlogs
+
+from pytorch_fid.fid_score import save_fid_stats, calculate_fid_given_paths
+from pytorch_fid.inception import InceptionV3
+
+sys.path.append(os.path.dirname(sys.path[0]))
+from utils.initializer import device_initializer
+
+logger = logging.getLogger(__name__)
+coloredlogs.install(level="INFO")
+
+
+def main(args):
+    logger.info(msg=f"[Note]: Input params: {args}")
+    device_id = args.use_gpu
+    paths = args.path
+    batch_size = args.batch_size
+    num_workers = args.num_workers
+    dims = args.dims
+    device = device_initializer(device_id=device_id)
+    # TODO: Check image size
+    # Compute fid
+    if args.save_stats:
+        save_fid_stats(paths=paths, batch_size=batch_size, device=device, dims=dims, num_workers=num_workers)
+        return
+
+    fid_value = calculate_fid_given_paths(paths=paths, batch_size=batch_size, device=device, dims=dims,
+                                          num_workers=num_workers)
+
+    logger.info(msg=f"The result of FID: {fid_value}")
+
+
+if __name__ == "__main__":
+    # Before calculating
+    # [Note]: We recommend resizing both sets of images to the same format, the same size, and the same number
+    parser = argparse.ArgumentParser()
+    # Function1: Generated image folder and dataset image folder
+    # Function2: Save stats input path and output path (use `--save_stats`)
+    parser.add_argument("path", type=str, nargs="*",
+                        default=["/your/generated/image/folder/or/stats/input/path",
+                                 "/your/dataset/image/folder/or/stats/output/path"],
+                        help="Paths to the generated images or to .npz statistic files")
+    # Batch size
+    parser.add_argument("--batch_size", type=int, default=8,
+                        help="Batch size for calculation.")
+    # Number of workers
+    parser.add_argument("--num-workers", type=int, default=0)
+    # Dimensionality of Inception features to use
+    # Option: 64/192/768/2048
+    parser.add_argument("--dims", type=int, default=2048,
+                        choices=list(InceptionV3.BLOCK_INDEX_BY_DIM),
+                        help="Dimensionality of Inception features to use. By default, uses pool3 features")
+    parser.add_argument("--save_stats", action="store_true",
+                        help="Generate an npz archive from a directory of samples. "
+                             "The first path is used as input and the second as output.")
+    # Set the use GPU in normal training (required)
+    parser.add_argument("--use_gpu", type=int, default=0)
+    args = parser.parse_args()
+    main(args)