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scott merged 6 commits from jazz/YOLOv8_test_example:fork into main 2026-09-17 11:26:36 -05:00
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# test
outputs `Yes` if the supplied image contains a bus and `No` if it does not
## usage
syntax: `./test.py [IMAGE]`
### example 1
testing with the following image:
![](img/bus.jpg)
```bash
./test.py img/bus.jpg
```
output:
```
image 1/1 /home/ja/git/YOLOv8_test_example/img/bus.jpg: 640x480 4 persons, 1 bus, 1 stop sign, 20.1ms
Speed: 1.0ms preprocess, 20.1ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 480)
Yes
Confidence: 87.3%
```
### example 2
testing with the following image:
![](img/notabus.png)
```bash
./test.py img/notabus.png
```
output:
```
image 1/1 /home/ja/git/YOLOv8_test_example/img/notabus.png: 384x640 (no detections), 17.4ms
Speed: 0.9ms preprocess, 17.4ms inference, 0.4ms postprocess per image at shape (1, 3, 384, 640)
No
```
### example 3
testing with the following image:
![](img/bus2.png)
```bash
./test.py img/bus2.png
```
output:
```
image 1/1 /home/ja/git/YOLOv8_test_example/img/bus2.png: 384x640 (no detections), 16.4ms
Speed: 1.1ms preprocess, 16.4ms inference, 0.3ms postprocess per image at shape (1, 3, 384, 640)
No
```
Note that another cartoon image of a bus did register as a bus.
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it works on pictures of busses but not the hand-drawn image i made.
This program tells you whether or not the selected image is a bus.
python3 test.py
To change the file to run the operation on, change this line in the source code: results = model("bus4.jpg")
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#!/usr/bin/env python3
import sys
from ultralytics import YOLO
image_path = sys.argv[1]
# Load the small pretrained YOLOv8 object-detection model.
model = YOLO("yolov8n.pt")
# Run object detection on a test image.
results = model("bus4.jpg")
results = model(image_path)
has_bus = False
max_confidence = 0.0