A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python.

Overview

c is for Camera

A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python.

The purpose of this project is to explore and understand the logic in the mechanisms of a camera by using object-oriented programming to represent real-world objects. It's also a way to appreciate the intricate mechanical logic embodied in a device like a camera.

'Canonet G-III QL17'

It aims towards completeness in its modelling of the real world. For example, if you open the back of the camera in daylight with a partially exposed film, it will ruin the film.

See the c is for Camera documentation.

A quick tour

Clone the repository:

git clone https://github.com/evildmp/C-is-for-Camera.git

or:

git clone [email protected]:evildmp/C-is-for-Camera.git

In the C-is-for-Camera directory, start a Python 3 shell.

>>> from camera import Camera
>>> c = Camera()

See the camera's state:

>>> c.state()
================== Camera state =================

------------------ Controls ---------------------
Selected speed:            1/120

------------------ Mechanical -------------------
Back closed:               True
Lens cap on:               False
Film advance mechanism:    False
Frame counter:             0
Shutter cocked:            False
Shutter timer:             1/128 seconds
Iris aperture:             ƒ/16
Camera exposure settings:  15.0 EV

------------------ Metering ---------------------
Light meter reading:        4096 cd/m^2
Exposure target:            15.0 EV
Mode:                       Shutter priority
Battery:                    1.44 V
Film speed:                 100 ISO

------------------ Film -------------------------
Speed:                      100 ISO
Rewound into cartridge:     False
Exposed frames:             0 (of 24)
Ruined:                     False

------------------ Environment ------------------
Scene luminosity:           4096 cd/m^2

Advance the film:

>>> c.film_advance_mechanism.advance()
On frame 0 (of 24)
Advancing film
On frame 1 (of 24)
Cocking shutter
Cocked

Release the shutter:

>>> c.shutter.trip()
Shutter openening for 1/128 seconds
Shutter closes
Shutter uncocked
'Tripped'

It's not possible to advance the mechanism twice without releasing the shutter:

>>> c.film_advance_mechanism.advance()
On frame 1 (of 24)
Advancing film
On frame 2 (of 24)
Cocking shutter
Cocked
>>> c.film_advance_mechanism.advance()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/daniele/Repositories/camera/camera.py", line 56, in advance
    raise self.AlreadyAdvanced
camera.AlreadyAdvanced

If you open the back in daylight it ruins the film:

>>> c.back.open()
Opening back
Resetting frame counter to 0
'Film is ruined'

Close the back and rewind the film:

>>> c.back.close()
Closing back
>>> c.film_rewind_mechanism.rewind()
Rewinding film
Playable Video Generation

Playable Video Generation Playable Video Generation Willi Menapace, Stéphane Lathuilière, Sergey Tulyakov, Aliaksandr Siarohin, Elisa Ricci Paper: ArX

Willi Menapace 136 Dec 31, 2022
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes

FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes This repository contains the source code accompanying the paper: FlexConv: C

Robert-Jan Bruintjes 96 Dec 12, 2022
Official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION.

IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION This is the official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSU

电线杆 14 Dec 15, 2022
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

Imbalanced Dataset Sampler Introduction In many machine learning applications, we often come across datasets where some types of data may be seen more

Ming 2k Jan 08, 2023
Snscrape-jsonl-urls-extractor - Extracts urls from jsonl produced by snscrape

snscrape-jsonl-urls-extractor extracts urls from jsonl produced by snscrape Usag

1 Feb 26, 2022
Pure python implementations of popular ML algorithms.

Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks

Alexis Gidiotis 3 Jan 10, 2022
PyTorch-based framework for Deep Hedging

PFHedge: Deep Hedging in PyTorch PFHedge is a PyTorch-based framework for Deep Hedging. PFHedge Documentation Neural Network Architecture for Efficien

139 Dec 30, 2022
Github project for Attention-guided Temporal Coherent Video Object Matting.

Attention-guided Temporal Coherent Video Object Matting This is the Github project for our paper Attention-guided Temporal Coherent Video Object Matti

71 Dec 19, 2022
An implementation of the paper "A Neural Algorithm of Artistic Style"

A Neural Algorithm of Artistic Style implementation - Neural Style Transfer This is an implementation of the research paper "A Neural Algorithm of Art

Srijarko Roy 27 Sep 20, 2022
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)

Realtime Multi-Person Pose Estimation By Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh. Introduction Code repo for winning 2016 MSCOCO Keypoints Cha

Zhe Cao 4.9k Dec 31, 2022
Code release for NeRF (Neural Radiance Fields)

NeRF: Neural Radiance Fields Project Page | Video | Paper | Data Tensorflow implementation of optimizing a neural representation for a single scene an

6.5k Jan 01, 2023
Code implementation of "Sparsity Probe: Analysis tool for Deep Learning Models"

Sparsity Probe: Analysis tool for Deep Learning Models This repository is a limited implementation of Sparsity Probe: Analysis tool for Deep Learning

3 Jun 09, 2021
Kinetics-Data-Preprocessing

Kinetics-Data-Preprocessing Kinetics-400 and Kinetics-600 are common video recognition datasets used by popular video understanding projects like Slow

Kaihua Tang 7 Oct 27, 2022
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

Deep High-Resolution Representation Learning for Human Pose Estimation (CVPR 2019) News [2020/07/05] A very nice blog from Towards Data Science introd

Leo Xiao 3.9k Jan 05, 2023
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo

Jialian Wu 54 Jan 06, 2023
Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Oral)

Pixel-Perfect Structure-from-Motion (ICCV 2021 Oral) We introduce a framework that improves the accuracy of Structure-from-Motion by refining keypoint

Computer Vision and Geometry Lab 831 Dec 29, 2022
In Search of Probeable Generalization Measures

In Search of Probeable Generalization Measures Exciting News! In Search of Probeable Generalization Measures has been accepted to the International Co

Mahdi S. Hosseini 6 Sep 11, 2022
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy

InferPy: Deep Probabilistic Modeling Made Easy InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top

PGM-Lab 141 Oct 13, 2022
Using VapourSynth with super resolution models and speeding them up with TensorRT.

VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi

111 Jan 05, 2023
A graph adversarial learning toolbox based on PyTorch and DGL.

GraphWar: Arms Race in Graph Adversarial Learning NOTE: GraphWar is still in the early stages and the API will likely continue to change. 🚀 Installat

Jintang Li 54 Jan 05, 2023