pra-dan

from polygraphy.backend.onnxrt import OnnxrtRunner, SessionFromOnnx
from polygraphy.backend.trt import TrtRunner, EngineFromNetwork, NetworkFromOnnxPath
from polygraphy.comparator import Comparator, DataLoader

model_path_1 = "yes_dynamo.onnx"
model_path_2 = "no_dynamo.onnx"

build_onnxrt_session_1 = SessionFromOnnx(model_path_1)
build_onnxrt_session_2 = SessionFromOnnx(model_path_2)
# build_engine = EngineFromNetwork(NetworkFromOnnxPath(model_path))

pra-dan

# Install DeepStream 5.1
- Flash JetPack 4.5.1 which comes installed with DeepStream 5.1.

# Install Prerequisites
## Install packages. Run `requirements.sh`
## Follow instructions given in `/opt/nvidia/deepstream/deepstream-5.1/sources/apps/sample_apps/deepstream_app/README` as follows:
sudo apt-get install libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev \
   libgstrtspserver-1.0-dev libx11-dev

# Obtain inference engine using `trtexec`

pra-dan

{
  "name": "POOPY",
  "symbol": "poopy",
  "description": "Test NFT",
  "seller_fee_basis_points": 10,
  "image": "https://github.com/matterport/Mask_RCNN/blob/master/images/2383514521_1fc8d7b0de_z.jpg",
  "animation_url": "https://www.arweave.net/efgh1234?ext=mp4",
  "external_url": "https://twitter.com/yellowpoophole",
  "attributes": [
    {

pra-dan

Observations (for bigger bot)

1. Related to Forward and Reverse Drive

# Drive codes
0x602: RIGHT DRIVE
0X601: LEFT DRIVE

# Acceleration Codes
Min V: 0xCC = 204
Max V: 0x6A = 106 # faster

pra-dan

import bpy
import os
from math import *
from mathutils import *

#set your own target here
target = bpy.data.objects['Cube']
cam = bpy.data.objects['Camera']
t_loc_x = target.location.x
t_loc_y = target.location.y

pra-dan

import bpy
import os
from math import *
from mathutils import *

#set your own target here
target = bpy.data.objects['Cube']
cam = bpy.data.objects['Camera']
t_loc_x = target.location.x
t_loc_y = target.location.y

pra-dan

1. Remove all entries with empty strings OR empty cells

for col in rawData.columns: # Iterate over all cols
  #print(f'col: {col}')  
  
  # Replace empty strings (if any), with NaN
  df[col].replace('', np.nan, inplace=True)
  
  # Remove all rows with any entry = NaN
 df.dropna(subset=[col], inplace=True)

pra-dan

# Install TensorFlow
!pip install tensorflow==1.11.0

# Get repository
!git clone https://github.com/mystic123/tensorflow-yolo-v3.git
%cd tensorflow-yolo-v3
!git checkout ed60b90

# Get coco.names
!wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names

pra-dan

# Note: The author has kept the weights and cfg files strictly in their respective directories.
# If you add yours, do place them in the same folders

!pip install onnx==1.6.0 onnx-tf==1.5.0
!pip install tensorflow-gpu==1.15.0

%cd repo
!wget "https://pjreddie.com/media/files/yolov3-tiny.weights" -O "/weights/" 
# The cfg file is already present in the repo.

pra-dan

# Install TensorFlow 1.13.1
!pip install tensorflow==1.13.1

# Get the repo
!git clone "https://github.com/jinyu121/DW2TF.git"
%cd DW2TF
!python3 main.py \
    --cfg "PATH_to_config/yolo-v2-tiny-coco.cfg" \
    --weights "PATH_to_weights/yolo-v2-tiny-coco.weights" \
    --output "content/" \