YOLOv8 latest improvement series The paper proposed by GSConv + Slim Neckr click here For detailed improvement tutorials and source code, click here! Click here! ! Click here! ! ! Station B: The source code of AI Academic Calling Beast is in the link in the album, and there is also a link in the […]
Tag: targets
YOLOV5 improvement – increase the detection layer of small targets, K-means clustering generation box
One of the reasons why YOLOv5 is not effective for small target detection is that the small target sample size is small, and the downsampling multiplier of YOLOv5 is large. Deeper feature maps make it difficult to learn features of small objects, so this paper proposes to add a small object detection layer to detect […]
Yolov5 optimization: multi-branch convolution module RFB, expanding the receptive field to improve the detection accuracy of small targets
Directory 1. Introduction to RFB-Net 2. RFB is introduced into yolov5 2.1 Modify commmon.py 2.2 Modify yolo.py 2.3 yolov5s_REF.yaml 1. Introduction to RFB-Net Paper: https://arxiv.org/pdf/1711.07767.pdf Code: https://github.com/ruinmessi/RFBNet Inspired by the Receptive Fields structure of human vision, this paper proposes RFB, taking the scale and eccentricity of RFs into consideration, and using a lightweight backbone network […]
Yolov8 optimization: multi-branch convolution module RFB, expanding the receptive field to improve the detection accuracy of small targets
1. Introduction to RFB-Net Paper: https://arxiv.org/pdf/1711.07767.pdf Code: GitHub – GOATmessi7/RFBNet: Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018 Inspired by the Receptive Fields structure of human vision, this paper proposes RFB, taking the scale and eccentricity of RFs into consideration, and using a lightweight backbone network can also extract high discriminative […]
Based on the full series of yolov5 models [n/s/m/l/x], a fine-grained detection and recognition system for 120 kinds of dog targets in Stanford was developed and constructed with different parameter levels
It is still relatively rare to develop and build a target detection system with more than 100 categories based on YOLOv5. Although in previous projects, the magnitude of birds has reached more than 100, but this type of task is relatively small. To simplify, the core purpose of this article is to develop a fine-grained […]
Two-wheel pan-tilt trolley realizes the function of tracking color targets
1. Function Description Install a camera on the R216a prototype. The example in this article will realize the function of the two-wheeled car autonomously looking for the color target through the two-degree-of-freedom platform. 2. Structure Description The R216a prototype is mainly composed of a two-wheel trolley and a 2-degree-of-freedom head . 3. Electronic hardware In […]
Play with SAM Semantic Segmentation (3) Save images of specific targets
1. Use OpenCV to display each mask the code import numpy as np import torch import matplotlib.pyplot as plt import cv2 from segment_anything import sam_model_registry, SamPredictor image = cv2.imread(‘notebooks/images/truck.jpg’) image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) sam_checkpoint = “models/sam_vit_b_01ec64.pth” model_type = “vit_b” device = “cuda” sam = sam_model_registry[model_type](checkpoint=sam_checkpoint) sam.to(device=device) predictor = SamPredictor(sam) input_point = np.array([[500, 375]]) input_label = […]
org.postgresql.util.PSQLException: Invalid targetServerType value: primary
Record the solution to this error: Specific error information: [ERROR com.zaxxer.hikari.pool.HikariPool:567]:HikariPool-1 – Exception during pool initialization. org.postgresql.util.PSQLException: Invalid targetServerType value: primary at org.postgresql.core.v3.ConnectionFactoryImpl.openConnectionImpl( ConnectionFactoryImpl.java:157) at org.postgresql.core.ConnectionFactory.openConnection(ConnectionFactory.java:49) at org.postgresql.jdbc.PgConnection.(PgConnection.java:195) at org.postgresql.Driver.makeConnection (Driver.java:454) at org.postgresql.Driver.connect(Driver.java:256) at com.zaxxer.hikari.util.DriverDataSource.getConnection(DriverDataSource.java:117) at com.zaxxer.hikari.util. DriverDataSource.getConnection(DriverDataSource.java:123) at com.zaxxer.hikari.pool.PoolBase.newConnection(PoolBase.java:365) at com.zaxxer.hikari.pool.PoolBase.newPoolEntry(PoolBase.java:194) at com .zaxxer.hikari.pool.HikariPool.createPoolEntry(HikariPool.java:460) at com.zaxxer.hikari.pool.HikariPool.checkFailFast(HikariPool.java:534) at com.zaxxer.hikari.pool.HikariPool. (HikariPool.java:115) at com.zaxxer.hikari.HikariDataSource.getConnection(HikariDataSource.java:112) at com.zaxxer.hikari.HikariDataSource$$FastClassBySpringCGLIB$$eeb1ae86.invoke() at […]
How to solve the problem of small targets in target detection?
Click “Xiaobai learns vision” above, and choose to add “Star” or “Stick“ Heavy dry goods, delivered as soon as possible By Nabil MADALI Compilation: ronghuaiyang Guide This paper introduces some methods and ideas for small target object detection. In deep learning object detection, especially in face detection, due to low resolution, blurred images, less information, […]
[Solved] maven packaging error: Please refer to XXXtargetsurefire-reports for the individual test results. And skip test packaging
When using maven to use package packaging, sometimes the following error occurs: There are test failures. Please refer to XXX/target/surefire-reports for the individual test results This indicates a packaging failure caused by a test failure. The solution is to skip the test packaging. 1. Command line form (universal) Command 1: mvn package -Dmaven.test.skip=true or Command […]