All Projects → rsomani95 → Shot Type Classifier

rsomani95 / Shot Type Classifier

Licence: other
Detecting cinema shot types using a ResNet-50

Projects that are alternatives of or similar to Shot Type Classifier

Deep Learning With Python
Deep learning codes and projects using Python
Stars: ✭ 195 (+78.9%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks, resnet
Grad Cam Tensorflow
tensorflow implementation of Grad-CAM (CNN visualization)
Stars: ✭ 261 (+139.45%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks, resnet
Pytorch Image Classification
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
Stars: ✭ 272 (+149.54%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks, resnet
Equivariant Transformers
Equivariant Transformer (ET) layers are image-to-image mappings that incorporate prior knowledge on invariances with respect to continuous transformations groups (ICML 2019). Paper: https://arxiv.org/abs/1901.11399
Stars: ✭ 68 (-37.61%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Audio classification
CNN 1D vs 2D audio classification
Stars: ✭ 65 (-40.37%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Gtsrb
Convolutional Neural Network for German Traffic Sign Recognition Benchmark
Stars: ✭ 65 (-40.37%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Keras model compression
Model Compression Based on Geoffery Hinton's Logit Regression Method in Keras applied to MNIST 16x compression over 0.95 percent accuracy.An Implementation of "Distilling the Knowledge in a Neural Network - Geoffery Hinton et. al"
Stars: ✭ 59 (-45.87%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Yolo resnet
Implementing YOLO using ResNet as the feature extraction network
Stars: ✭ 82 (-24.77%)
Mutual labels:  jupyter-notebook, resnet
Cnn Interpretability
🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease
Stars: ✭ 68 (-37.61%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Automatic Image Captioning
Generating Captions for images using Deep Learning
Stars: ✭ 84 (-22.94%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
3dunet abdomen cascade
Stars: ✭ 91 (-16.51%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Pneumonia Detection From Chest X Ray Images With Deep Learning
Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models
Stars: ✭ 64 (-41.28%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Deep Ranking
Learning Fine-grained Image Similarity with Deep Ranking is a novel application of neural networks, where the authors use a new multi scale architecture combined with a triplet loss to create a neural network that is able to perform image search. This repository is a simplified implementation of the same
Stars: ✭ 64 (-41.28%)
Mutual labels:  convolutional-neural-networks, resnet
Sru Deeplearning Workshop
دوره 12 ساعته یادگیری عمیق با چارچوب Keras
Stars: ✭ 66 (-39.45%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Cnn graph
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Stars: ✭ 1,110 (+918.35%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Age Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Stars: ✭ 1,195 (+996.33%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Trained Ternary Quantization
Reducing the size of convolutional neural networks
Stars: ✭ 90 (-17.43%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Fakeimagedetector
Image Tampering Detection using ELA and CNN
Stars: ✭ 93 (-14.68%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Sigmoidal ai
Tutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal
Stars: ✭ 103 (-5.5%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks
Convisualize nb
Visualisations for Convolutional Neural Networks in Pytorch
Stars: ✭ 57 (-47.71%)
Mutual labels:  jupyter-notebook, convolutional-neural-networks

AI For Filmmaking

Code for the blog post AI for Filmmaking. Detect cinematic shot types in images using a pre-trained ResNet-50.

This model recognises 6 shot types:

1. Extreme Wide Shot

2. Long Shot

3. Medium Shot

4. Medium Close Up

5. Close Up

6. Extreme Close Up


In the not so distant future, it will also recognise:

Wide Shots

Medium Long Shots

Requirements

fastai — Installation instructions here. You can use this code without a GPU.

Usage

After downloading the directory, run bash get_data_model.sh to download the model and the validation set. A dummy training set is downloaded too to enable the generation of heatmaps.

Predict Shot Types

python get-preds.py                     \
    --path_base  ~/shot-type-classifier \
    --path_img   ~/images               \
    --path_preds ~/images/preds         \

Where path_base is the directory path, path_img the path to the images you want to evaluate, and path_preds where you'd like to store the predictions (.csv files). The script create the ~/images/preds folder if it doesn't exist.

Heatmaps

python get-heatmaps.py                 \
    --path_base ~/shot-type-classifier \
    --path_img  ~/images               \
    --path_hms  ~/images/heatmaps      \
    --alpha 0.8

Where path_base is the directory path, path_img the path to the images you want to evaluate, path_hms where you'd like to store the heatmaps, and alpha the blending value of the heatmap with the original image. An alpha value of 1.0 produces the heatmap only. The script create the ~/images/heatmaps folder if it doesn't exist.

License

This repository is released under the Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0). See here for more details.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].