Rebase Python example from ioir123ju/tkDNN/master/

2020-08-22 12:53:59 -07:00
parent 38106a9495 e68b0e7bc7
commit b2b5e2db98
9 changed files with 424 additions and 4 deletions
@@ -208,6 +208,7 @@ Once you have succesfully created your rt file, run the demo:
 ./demo yolo4_fp32.rt ../demo/yolo_test.mp4 y
 ```
 In general the demo program takes 7 parameters:
+
 ```
 ./demo <network-rt-file> <path-to-video> <kind-of-network> <number-of-classes> <n-batches> <show-flag>
 ```
@@ -225,6 +226,13 @@ N.b. By default it is used FP32 inference

 ![demo](https://user-images.githubusercontent.com/11562617/72547657-540e7800-388d-11ea-83c6-49dfea2a0607.gif)

+## PYTHON
+To run the an object detection demo with python (example with yolov4):
+```
+python darknetTR.py build/yolo4_fp16.rt --video=demo/yolo_test.mp4
+```
+
+
 ### FP16 inference

 To run the an object detection demo with FP16 inference follow these steps (example with yolov3):