DunnBC22 commited on
Commit
2c34326
1 Parent(s): c828e63

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +21 -3
README.md CHANGED
@@ -21,17 +21,21 @@ This model is a fine-tuned version of [hustvl/yolos-tiny](https://huggingface.co
21
 
22
  ## Model description
23
 
24
- More information needed
25
 
26
  **If you intend on trying this project yourself, I highly recommend using (at least) the yolos-small checkpoint.
27
 
28
  ## Intended uses & limitations
29
 
30
- More information needed
31
 
32
  ## Training and evaluation data
33
 
34
- More information needed
 
 
 
 
35
 
36
  ## Training procedure
37
 
@@ -48,6 +52,20 @@ The following hyperparameters were used during training:
48
 
49
  ### Training results
50
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
51
 
52
  ### Framework versions
53
 
 
21
 
22
  ## Model description
23
 
24
+ For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Object%20Detection/Brain%20Tumors/Brain_Tumor_m2pbp_Object_Detection_YOLOS.ipynb
25
 
26
  **If you intend on trying this project yourself, I highly recommend using (at least) the yolos-small checkpoint.
27
 
28
  ## Intended uses & limitations
29
 
30
+ This model is intended to demonstrate my ability to solve a complex problem using technology.
31
 
32
  ## Training and evaluation data
33
 
34
+ Dataset Source: https://huggingface.co/datasets/Francesco/brain-tumor-m2pbp
35
+
36
+ **Example**
37
+
38
+ ![Example Image](https://raw.githubusercontent.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/main/Computer%20Vision/Object%20Detection/Brain%20Tumors/Images/Example.png)
39
 
40
  ## Training procedure
41
 
 
52
 
53
  ### Training results
54
 
55
+ | Metric Name | IoU | Area | maxDets | Metric Value |
56
+ |:-----:|:-----:|:-----:|:-----:|:-----:|
57
+ | Average Precision (AP) | IoU=0.50:0.95 | area= all | maxDets=100 | 0.185
58
+ | Average Precision (AP) | IoU=0.50 | area= all | maxDets=100 | 0.448
59
+ | Average Precision (AP) | IoU=0.75 | area= all | maxDets=100 | 0.126
60
+ | Average Precision (AP) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.001
61
+ | Average Precision (AP) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.080
62
+ | Average Precision (AP) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.296
63
+ | Average Recall (AR) | IoU=0.50:0.95 | area= all | maxDets= 1 | 0.254
64
+ | Average Recall (AR) | IoU=0.50:0.95 | area= all | maxDets= 10 | 0.353
65
+ | Average Recall (AR) | IoU=0.50:0.95 | area= all | maxDets=100 | 0.407
66
+ | Average Recall (AR) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.036
67
+ | Average Recall (AR) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.312
68
+ | Average Recall (AR) |IoU=0.50:0.95 | area= large | maxDets=100 | 0.565
69
 
70
  ### Framework versions
71