From 0c379c3f7288f0537152bf8629bf5ecbe1fe9662 Mon Sep 17 00:00:00 2001
From: Ruozhu <ruozhu.li@wur.nl>
Date: Thu, 24 Apr 2025 11:55:42 +0200
Subject: [PATCH] revise readme file

---
 README.md                 |  33 +++++++++++++++------------------
 ~$experiment_results.xlsx | Bin 0 -> 165 bytes
 2 files changed, 15 insertions(+), 18 deletions(-)
 create mode 100644 ~$experiment_results.xlsx

diff --git a/README.md b/README.md
index 3ba1c03..bc60163 100644
--- a/README.md
+++ b/README.md
@@ -77,28 +77,25 @@ See `experiment_results.xlsx` for:
 ![Pipeline Flowchart](images/pipeline.png)
 
 ## Summary Table
-| index        | type      | backbone  | scale count(s) | augmentation               | training time of 20 epochs | mAP on test set |
-|--------------|-----------|-----------|----------------|----------------------------|----------------------------|------------------|
-| experiment_1 | one-step  | ResNet-18 | 1              | none                       | 2m 38s                     | 0.1068           |
-| experiment_2 | one-step  | ResNet-18 | 2              | none                       | 2m 43s                     | 0.4435           |
-| experiment_3 | one-step  | ResNet-34 | 2              | none                       | 2m 33s                     | 0.4595           |
-| experiment_4 | one-step  | ResNet-50 | 2              | none                       | 2m 60s                     | 0.4348           |
-| experiment_5 | one-step  | ResNet-34 | 3              | none                       | 2m 37s                     | 0.4215           |
-| experiment_6 | one-step  | ResNet-34 | 2              | aggressive, *3 training data| 7m 32s                     | 0.5455           |
-| experiment_7 | two-step  | ResNet-34 | 2              | aggressive, *3 training data| detector: 7m 29s<br>classifier: 6m 16s | 0.4461           |
+| Index | Type | Training Time of 20 Epochs | Performance: mAP on Validation Set | Performance: mAP on Test Set |
+|-------|------|----------------------------|-----------------------------------|------------------------------|
+| experiment_1 | one-step | 2m 38s | 0.198 | 0.107 |
+| experiment_2 | one-step | 2m 43s | 0.637 | 0.444 |
+| experiment_3 | one-step | 2m 33s | 0.541 | 0.460 |
+| experiment_4 | one-step | 2m 60s | 0.690 | 0.435 |
+| experiment_5 | one-step | 2m 37s | 0.717 | 0.422 |
+| experiment_6 | one-step | 7m 32s | 0.696 | 0.545 |
+| experiment_7 | two-step | detector: 7m 29s<br>classifier: 6m 16s | 0.801 | 0.446 |
 
 ## Qualitative Results
 ![Visualisation of experiment_6](images/visualisation.png)
 
 ## Key Insights
 
-* Multi-scale detection significantly improves performance on mixed-size fruits.
-* ResNet-34 has a moderate depth and number of parameters, offering a good balance for small datasets. It extracts features better than ResNet-18 but is less prone to overfitting than ResNet-50.
-* Aggressive color jittering helps models generalize better across challenging lighting and backgrounds, requiring more time but resulting in a higher mAP.
-* Two-step detection is more modular but does not significantly outperform optimized one-step models in this task.
+* Multi-scale detection significantly improves performance on fruits with size variants.
+* ResNet-34 offers a good balance for our datasets. It extracts features better than ResNet-18 but is less prone to overfitting than ResNet-50.
+* Color jittering helps models perform better across challenging backgrounds.
+* Two-step method does not significantly outperform optimized one-step models in this task.
 
-## Link to Report
-
-Full report: //TODO
-
-Code Repository: https://git.wur.nl/wei044/deeplearning-mbe-8
\ No newline at end of file
+## Code Repository
+ https://git.wur.nl/wei044/deeplearning-mbe-8
\ No newline at end of file
diff --git a/~$experiment_results.xlsx b/~$experiment_results.xlsx
new file mode 100644
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