yolo

问题 I will use yolo weights in android so I plan to convert yolo weights file to tflite file. I use this code in anaconda prompt because I downloaded keras library in env. activate env python convert.py yolov3.cfg yolov3.weights model_data/yolo.h5 Finally, it did.Saved Keras model to model_data/yolo.h5 And I'm going to convert this h5 file to tflite file in jupyter notebook with this code. model = tf.keras.models.load_model("./yolo/yolo.h5", compile=False) converter = tf.lite.TFLiteConverter.from

问题 I am trying to run YOLOv3 on Visual Studio 2019 using CUDA 10.2 with cuDNN v7.6.5 on Windows 10 using NVidia GeForce 930M. Here is part of the code I used. #include <fstream> #include <sstream> #include <iostream> #include <opencv2/dnn.hpp> #include <opencv2/imgproc.hpp> #include <opencv2/highgui.hpp> using namespace cv; using namespace dnn; using namespace std; int main() { // Load names of classes string classesFile = "coco.names"; ifstream ifs(classesFile.c_str()); string line; while

问题 I have Yolo format bounding box annotations of objects saved in a .txt files. Now I want to load those coordinates and draw it on the image using OpenCV , but I don’t know how to convert those float values into OpenCV format coordinates values I tried this post but it didn’t help, below is a sample example of what I am trying to do Code and output import matplotlib.pyplot as plt import cv2 img = cv2.imread(<image_path>) dh, dw, _ = img.shape fl = open(<label_path>, 'r') data = fl.readlines()

问题 I have Yolo format bounding box annotations of objects saved in a .txt files. Now I want to load those coordinates and draw it on the image using OpenCV , but I don’t know how to convert those float values into OpenCV format coordinates values I tried this post but it didn’t help, below is a sample example of what I am trying to do Code and output import matplotlib.pyplot as plt import cv2 img = cv2.imread(<image_path>) dh, dw, _ = img.shape fl = open(<label_path>, 'r') data = fl.readlines()

问题 I am trying to understand how Darknet works, and I was looking at the yolov3-tiny configuration file, specifically the layer number 13 (line 107). [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky The size of the kernel is 1x1, the stride is 1 and the padding is 1 too. When I load the network using darknet, it indicates that the output width and height are the same as the input: 13 conv 256 1 x 1/ 1 13 x 13 x1024 -> 13 x 13 x 256 However, shouldn't the width

问题 I am trying to understand the .cfg file of YOLOv2. I didn't understand steps=-1,100,80000,100000 scales=.1,10,.1,.1 Can someone explain me this. 回答1: steps is a checkpoints (number of iterations) at which scales will be applied. scales is a coefficients at which learning_rate will be multiplied at this checkpoints. Determines how the learning_rate will be changed during increasing number of iterations during training. Both of them are related to each other and they have the same amount. steps

问题 I'm trying to make object detection software with yolo and this error is popping and I am so lost please can anyone help me !! (the code not complete and sorry if there are any mistakes in this post cus I am new Stackoverflow).the tutorial is from here Traceback (most recent call last): File "d:/opencv/objdetect_yolo.py", line 66, in <module> findobj(output,img) File "d:/opencv/objdetect_yolo.py", line 33, in findobj cofidence = scores[classId] IndexError: index 14708 is out of bounds for

问题 Hy! I am annotating image data through an online plateform which is generating output coordinates like this: bbox":{"top":634,"left":523,"height":103,"width":145} However, i want to use this annotation to train Yolo. So, I have to convert it in yolo format like this: 4 0.838021 0.605556 0.177083 0.237037 In this regard, i need help about how to convert it. 回答1: Here, For the size you need to pass the (w,h) and the for the box you need to pass (x,x+w, y, y+h) https://github.com/ivder

问题 I need to run my model in NVIDIA JETSON T2, So I converted my working yoloV3 model into tensorRT(.trt format)( https://towardsdatascience.com/have-you-optimized-your-deep-learning-model-before-deployment-cdc3aa7f413d )This link mentioned helped me to convert the Yolo model into .trt .But after converting the model to .trt model I needed to test if it works fine (i.e) If the detection is good enough. I couldn't find any sample code for loading and testing .trt model. If anybody can help me ,

问题 I need to run my model in NVIDIA JETSON T2, So I converted my working yoloV3 model into tensorRT(.trt format)( https://towardsdatascience.com/have-you-optimized-your-deep-learning-model-before-deployment-cdc3aa7f413d )This link mentioned helped me to convert the Yolo model into .trt .But after converting the model to .trt model I needed to test if it works fine (i.e) If the detection is good enough. I couldn't find any sample code for loading and testing .trt model. If anybody can help me ,