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Face detection with OpenCV and deep learning - PyImageSearch
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From raw images to real-time predictions with Deep Learning
WitrynaVideo Classification with a CNN-RNN Architecture. Author: Sayak Paul Date created: 2024/05/28 Last modified: 2024/06/05 Description: Training a video classifier with transfer learning and a recurrent model on the UCF101 dataset. View in Colab • GitHub source. This example demonstrates video classification, an important use-case with … Witryna14 mar 2024 · Code for GUI and mapping with emojis. Create a folder named emojis and save the emojis corresponding to each of the seven emotions in the dataset. Paste the below code in gui.py and run the file. import tkinter as tk. from tkinter import *. import cv2. Witryna26 lut 2024 · From there, open up a terminal and execute the following command: $ python detect_faces.py --image rooster.jpg --prototxt deploy.prototxt.txt \ --model res10_300x300_ssd_iter_140000.caffemodel. Figure 3: My face is detected in this image with 74% confidence using the OpenCV deep learning face detector. grand shopping messejana cinema