Instructions to use thangkt/PCB-Prune-YOLO-P20-Direct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use thangkt/PCB-Prune-YOLO-P20-Direct with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("thangkt/PCB-Prune-YOLO-P20-Direct") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- validation/metrics_val.csv +8 -0
- validation/metrics_val.json +59 -0
validation/metrics_val.csv
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
scope,precision,recall,mAP50,mAP50-95,class_id,class_name
|
| 2 |
+
overall,0.9621363400345814,0.9618648012811436,0.981835107441035,0.7671004007137501,,
|
| 3 |
+
class,0.9529199134123715,0.9565217391304348,0.9770359761624102,0.7043664929458436,0.0,open
|
| 4 |
+
class,0.9251284155923986,0.9360815847860002,0.9592670872901112,0.6773643413837104,1.0,short
|
| 5 |
+
class,0.9395938475684601,0.9612676056338029,0.9860887320896216,0.7590634675461975,2.0,mousebite
|
| 6 |
+
class,0.9836201600941977,0.9567099567099567,0.9845608255112044,0.720746974243411,3.0,spur
|
| 7 |
+
class,0.9951966750837129,0.9819424608491363,0.9948106436760856,0.8870177787124026,4.0,copper
|
| 8 |
+
class,0.9763590284563466,0.9786654605775313,0.9892473799167769,0.8540433494509359,5.0,pin-hole
|
validation/metrics_val.json
ADDED
|
@@ -0,0 +1,59 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"split": "val",
|
| 3 |
+
"overall": {
|
| 4 |
+
"precision": 0.9621363400345814,
|
| 5 |
+
"recall": 0.9618648012811436,
|
| 6 |
+
"mAP50": 0.981835107441035,
|
| 7 |
+
"mAP50-95": 0.7671004007137501
|
| 8 |
+
},
|
| 9 |
+
"per_class": [
|
| 10 |
+
{
|
| 11 |
+
"class_id": 0,
|
| 12 |
+
"class_name": "open",
|
| 13 |
+
"precision": 0.9529199134123715,
|
| 14 |
+
"recall": 0.9565217391304348,
|
| 15 |
+
"mAP50": 0.9770359761624102,
|
| 16 |
+
"mAP50-95": 0.7043664929458436
|
| 17 |
+
},
|
| 18 |
+
{
|
| 19 |
+
"class_id": 1,
|
| 20 |
+
"class_name": "short",
|
| 21 |
+
"precision": 0.9251284155923986,
|
| 22 |
+
"recall": 0.9360815847860002,
|
| 23 |
+
"mAP50": 0.9592670872901112,
|
| 24 |
+
"mAP50-95": 0.6773643413837104
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"class_id": 2,
|
| 28 |
+
"class_name": "mousebite",
|
| 29 |
+
"precision": 0.9395938475684601,
|
| 30 |
+
"recall": 0.9612676056338029,
|
| 31 |
+
"mAP50": 0.9860887320896216,
|
| 32 |
+
"mAP50-95": 0.7590634675461975
|
| 33 |
+
},
|
| 34 |
+
{
|
| 35 |
+
"class_id": 3,
|
| 36 |
+
"class_name": "spur",
|
| 37 |
+
"precision": 0.9836201600941977,
|
| 38 |
+
"recall": 0.9567099567099567,
|
| 39 |
+
"mAP50": 0.9845608255112044,
|
| 40 |
+
"mAP50-95": 0.720746974243411
|
| 41 |
+
},
|
| 42 |
+
{
|
| 43 |
+
"class_id": 4,
|
| 44 |
+
"class_name": "copper",
|
| 45 |
+
"precision": 0.9951966750837129,
|
| 46 |
+
"recall": 0.9819424608491363,
|
| 47 |
+
"mAP50": 0.9948106436760856,
|
| 48 |
+
"mAP50-95": 0.8870177787124026
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"class_id": 5,
|
| 52 |
+
"class_name": "pin-hole",
|
| 53 |
+
"precision": 0.9763590284563466,
|
| 54 |
+
"recall": 0.9786654605775313,
|
| 55 |
+
"mAP50": 0.9892473799167769,
|
| 56 |
+
"mAP50-95": 0.8540433494509359
|
| 57 |
+
}
|
| 58 |
+
]
|
| 59 |
+
}
|