Closed DanilZittser closed 2 years ago
Can you please point me to the source of edgetpu model you are using and try the below steps:
git clone https://github.com/google-coral/pycoral.git
cd pycoral
bash examples/install_requirements.sh detect_image.py
mendel@queen-shrimp:~/pycoral$ python3 examples/detect_image.py --model test_data/ssd_mobilenet_v2_coco_quant_postprocess_edgetpu.tflite --labels test_data/coco_labels.txt --input test_data/grace_hopper.bmp --output ${HOME}/grace_hopper_processed.bmp
----INFERENCE TIME----
Note: The first inference is slow because it includes loading the model into Edge TPU memory.
41.56 ms
16.21 ms
15.27 ms
13.50 ms
15.66 ms
-------RESULTS--------
tie
id: 31
score: 0.83984375
bbox: BBox(xmin=227, ymin=419, xmax=292, ymax=541)
person
id: 0
score: 0.8046875
bbox: BBox(xmin=2, ymin=4, xmax=513, ymax=595)
Thanks!
I get the same result as you:
But in detection README.md the following problem:
What is the reason of this behavior?
It's because detection README.md is using the old model from edgetpu repo. Please get the updated models form test_data repo. Thanks!
Description
Hi to all!
Why model often predict same score for various objects?
Below code snippet from detection README.md
I have a similar situation in my custom dataset: many identical scores.
Click to expand!
### Issue Type Support ### Operating System Mendel Linux ### Coral Device Dev Board ### Other Devices _No response_ ### Programming Language Python 3.7 ### Relevant Log Output _No response_