Deep learning lecture
(tensor flow based..)
1. logistic classification
2. stochastic optimization
3. general data practices to train models( data & parameter tuning)
part 2. (we're going to go deeper)
1. Deep networks
2. Regularization (to train even bigger models)
part 3. ( will be a deep dive into image and convolutional models)
1. convolutional networks
part 4. (all about text and sequence in general)
2. recurrent models
deep learning study (introduction) #1
CUDA_ARCH_BIN Table for gpu type Jetson Products GPU Compute Capability Jetson AGX Xavier 7.2 Jetson Nano 5.3 Jetson TX2 6.2 Jetson TX1 5.3 ...
put a explicit parameter name like: from sklearn.utils import class_weight class_weights = class_weight.compute_class_weight( class_weight...
look at the code! ^^ .. #load image tif_path = './input_img.tif' #open image pil_image = Image. open ( tif_path ) #change dpi in...
In past, I wrote an articel about YUV 444, 422, 411 introduction and yuv <-> rgb converting example code. refer to this page -> ht...
This is dithering example, it make image like a stippling effect. I referenced to blew website. wiki page: https://en.wikipedia.org/wik...
make well divided linear coordinate And make pair coordinate Please see code for detail explanation. import numpy as np import cv2 ...
input image output image source code import cv2 as cv import numpy as np import sys import random #read image img = ...
Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul...
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm...
Just see the code It's not difficult. ... ... import cv2 import numpy as np ... def lambda_handler(event, context): # TODO i...