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https://github.com/hnz1102/timeleapcam

Time Leap Cam - Super Long Term Time-Lapse Camera and Monitoring by OpenAI
https://github.com/hnz1102/timeleapcam

autofocus cam cloudflare emmc esp32 esp32s3 gpt-4o idf kicad line-messaging-api lipo-battery openai ov5640 pcbway qi-charger rust stl-containers time-lapse-cam touch-switch wifi-network

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Time Leap Cam - Super Long Term Time-Lapse Camera and Monitoring by OpenAI

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README 

        


  
Time Leap Cam


  


    

  





# Time Leap Cam - Super Long Term Time-Lapse Camera and Monitoring by OpenAI



## Overview

The TIME LEAP CAM is an autofocus camera designed for long-duration time-lapse photography. Named for its ability to "leap" through time, this camera is ideal for monitoring over extended periods. It operates on battery power and features a DeepSleep mode to conserve energy when not actively shooting. Images are stored on a 64GB eMMC within one of eleven designated folders.



## What's New!

- 2024-08-12, If you want use on the XIAO ESP32S3 Sense module, please refer to the [XIAO_ESP32S3_SENSE branch](https://github.com/hnz1102/timeleapcam/tree/XIAO_ESP32S3_SENSE).

![XIAO_ESP32S3_SENSE](doc/xiaos3s.jpg)



Update v0.3.3

- Improved the eMMC writing speed. The eMMC writing speed is improved by background writing. In the HD resolution, the writing speed is improved 28fps to 30fps. In the Full HD resolution, the writing speed is improved 6fps to 8fps. 

- JPEG quality can be set from 4 to 40. The default is 12. This value is high quality to set the value to 4. In the HD resolution, JPEG quality is set to less than 12, the writing speed is slower than 30fps. If you want to capture the image at 30fps, set the JPEG quality to 12 or more.

- If you want to direct write the image to the eMMC, set the 'Direct Write Mode' to checked. The image is directly written to the eMMC without the frame buffer. The writing speed is decreased. The default is unchecked.

- Changed the Allocate Unit Size to 32KB for the eMMC writing speed at the v0.3.3.



Update v0.3.2

- Add the 'System Temperature' to the status report. The temperature is measured by the internal temperature sensor of ESP32S3.

- Fixed the bug that when one-shot capture, the preview image is not displayed on the web.



Update v0.3.1

- Added the movie shooting function. The movie is created by combining the images taken at the specified cycle. 

 Capture Frames At Once (sec): The number of frames to capture at once. The default is 0, which means that the image is captured one by one. If you set it to 1, the image is captured during the 1 sec. If you set image resolution to VGA, the image is captured by 27 fps. HD is 15 - 27 fps. Full HD is 6 fps.

- Capture images are stored by appending the file. If you set to "Over Write Save", the image is overwritten. 

- Added the Open AI model 'GPT-4o mini' selection. The default is 'GPT-4o'. You can select the model from GPT-4o, GPT-4 Turbo, GPT-4o mini.

- If touch the button during 3 secs on the back, the camera starts the movie shooting. The movie shooting is stopped when the button is touched again.

- Improved the writing speed of the eMMC.

- Change the Report Interval: The default is 3600 sec. The report interval is changed to 3600 sec. The status report is sent to LINE when the specified cycle is reached.

- Camera interface is changed. Power Down, Reset pin is removed. In previous version, the power down pin and reset

pin are assigned by dumy GPIO pin. The 'esp-camera-rs' driver must be updated to the latest version.

- Fixed the bug that captured images are broken when the camera is in the DeepSleep mode. v0.3.1 is the stable version.

- Capturing clock is changed to 5MHz or 25MHz. The default is 5MHz when one image captured. When the movie is captured, the clock is changed to 25MHz.

- Changed the number of the frame buffer is 2. v0.3.0 set the number of the frame buffer to 3. But the eMMC writing speed is not enough to write the image to the eMMC. Since the eMMC writing speed is improved, the number of the frame buffer is changed to 2.

- Changed allocate_unit_size to 4096 for the eMMC writing speed at the v0.3.1.

- Fixed the bug that captured images are deleted when the camera is in the DeepSleep mode. v0.3.1 is fixed the bug.



Update v0.2.0

- Updated the UI for the configuration screen.

- Added the function to send a notification as status to LINE when the specified cycle is reached.

- Added the function to check the preview image on the web.

- Added images are uploaded to Cloudflare Images for private storage with signed URL.

- Added images are automatically deleted from the Cloudflare Images after 1 days.

- Added images can be downloaded as a compressed image from this camera on the web. (PC browser only)

- Added the function to check the remaining battery level on the web.

- Added the function to check the WiFi signal level on the web.

- Added the function to limit the time-lapse shooting time.

- Added the function to shoot when the camera touches the button during 3 secs on the back.



New Container Design

- The new container design is added for the camera

![Container](doc/newcontainer-s.jpg)



## Features

- **Autofocus Capability**: Ensures clear images over long shooting intervals.

- **Energy Efficiency**: Utilizes DeepSleep mode for minimal power consumption (less than 440uA, 1.5mW).

- **Wireless Charging**: Supports Qi wireless charging and automatically stops charging when full.

- **Water Resistance**: Suitable for outdoor use with splash resistance.

- **Advanced Notifications**: Uses OpenAI's GPT-4o/GPT-4o mini for image recognition and sends notifications via LINE when specific conditions are met.

- **Natural Language Configuration**: Set notification conditions in multiple languages through a simple interface.

- **Touch-Activated Web Server**: Access settings via a browser with automatic return to sleep mode after 5 minutes of inactivity.

- **Time Synchronization**: Uses NTP for automatic time adjustment when connected to WiFi, with RTC to maintain time offline.



## Specification

- **Resolution**: Up to 2592x1944 (QSXGA)

- **Sensor**: OV5640 5M pixel sensor

- **SoC Module**: ESP32-S3-WROOM-1-N16R8 (160MHz, 512KB SRAM, 16MB Flash, 8MB PSRAM)

- **Battery**: 3.7V LiPo 1100mAh

- **Storage**: 64GB eMMC

- **Connectivity**: WiFi 2.4GHz

- **Charging**: Qi wireless charging compatible

- **Dimensions**: 78(W) x 79(H) x 68(D) mm Box



## Usage

To use the TIME LEAP CAM, place it on a Qi wireless charger to charge power. Configure the camera settings such as shooting interval, time, and resolution through a web browser connected via WiFi. The camera can be activated from sleep mode by touching the screw on the back, which launches the web server for configuration.



## Options

- **Folder Selection**: Choose from 11 different folders for storing images.

- **Image Resolution**: Selectable up to QSXGA (2592x1944).

- **Notification Conditions**: Set via natural language input on the configuration screen.



## Notes

- **Water Immersion**: The camera is not designed to withstand full submersion in water.

- **API Keys Required**: To use the image recognition and notification features, obtain API keys from OpenAI, CloudFlare Images, and LINE Messaging API.

- **Internet Connection**: Required for using advanced features like image recognition and notifications. Time-lapse functionality is available without WiFi.



For API keys and more information, visit:

- OpenAI API: [https://openai.com/index/openai-api/](https://openai.com/index/openai-api/)

- CloudFlare Images: [https://developers.cloudflare.com/images/about](https://developers.cloudflare.com/images/about)

- LINE Messaging API: [https://developers.line.biz/en/docs/messaging-api/](https://developers.line.biz/en/docs/messaging-api/)

# How to build from code and Install to the unit.



Using Ubuntu 22.04.3 LTS and ESP-IDF V5.2.1



## Prerequisites

Before proceeding with the installation, ensure that your system meets the following requirements:

- Operating System: Linux-based distribution

- Required Packages: git, python3, python3-pip, gcc, build-essential, curl, pkg-config, libudev-dev, libtinfo5, clang, libclang-dev, llvm-dev, udev, libssl-dev, python3.10-venv



## Installation Steps



### 1. System Update and Package Installation

Update your system and install the necessary packages using:

```bash

sudo apt update && sudo apt -y install git python3 python3-pip gcc build-essential curl pkg-config libudev-dev libtinfo5 clang libclang-dev llvm-dev udev libssl-dev python3.10-venv

```



### 2. Rust Installation

Install Rust programming language and Cargo package manager:

```bash

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

```

After installation, activate Rust by sourcing the environment:

```bash

. "$HOME/.cargo/env"

```



### 3. Additional Tools Installation

Install the following Rust tools:

- ldproxy

- espup

- cargo-espflash



Use the following commands:

```bash

cargo install ldproxy

cargo install espup

cargo install cargo-espflash

```

2024-08-12, cargo-espflash can not be compiled.

If you have an error, use the following command.

```bash

cargo install cargo-binstall

cargo binstall cargo-espflash 

```



### 4. ESP Environment Setup

Run the following command to install and update the Espressif Rust ecosystem:

```bash

espup install

espup update

```

Set up environment variables:

```bash

. ./export-esp.sh

```



### 5. Udev Rules Configuration

Configure udev rules for device permissions:

```bash

sudo sh -c 'echo "SUBSYSTEMS==\"usb\", ATTRS{idVendor}==\"303a\", ATTRS{idProduct}==\"1001\", MODE=\"0666\"" > /etc/udev/rules.d/99-esp32.rules'

sudo udevadm control --reload-rules

sudo udevadm trigger

```



### 6. Clone Repository

Clone the TimeLeapCam repository:

```bash

git clone https://github.com/hnz1102/timeleapcam.git

cd timeleapcam/code/

```



### 7. Setting WiFi SSID, Password, etc.

Change the following the configuration file.

```bash

cfg.toml



[timeleapcam]

wifi_ssid = ""  # Set your AP SSID

wifi_psk = "" # Set your AP Password

http_server = "" # NOT USED

resolution = "8"

track_id = "0"

timezone_offset = "9"

auto_capture = "false"

idle_in_sleep_time = "300"

duration = "0"

api_key = "" # Set your OpenAI API Key

model = "gpt-4o"

query_openai = "false"

query_prompt = "If heavy rain is expected in 30 minutes, please include a 'NOTICE' with the reason in your reply. If not, simply respond with 'NONE'. Heavy rain is defined as 30mm/h or more."

post_account = "" # Set your LINE Account ID

post_access_token = "" # Set your LINE Access Token

storage_account = "" # Set your Cloudflare Account ID

storage_access_token = "" # Set your Cloudflare Access Token

storage_signed_key = "" # Set your Cloudflare Image Signed Key

post_message_trigger = "NOTICE"

autofocus_once = "true"

status_report = "false"

status_report_interval = "3600"

post_interval = "3600"

leap_day = "-1"

leap_hour = "-1"

leap_minute = "-1"

capture_frames_at_once = "0"

overwrite_saved = "false"

```



### 8. Build and Flash

Build the project and flash it to your device:

```bash

cargo build --release

cargo espflash flash --release --monitor

```

At the first boot, the device will format the eMMC and create the necessary folders. This process may take a few minutes.



## Schematic, PCB Gabar and Container 3D Data



There is a Schematic data in the hardware directory including 3D printing data. 



![board](doc/board.jpg)



![container](doc/container.jpg)



### New Cover and Base for the Camera

![New-Cover](doc/newcover-s.jpg)



Base for the camera is also available for 3D printing. base-v14.stl is the latest version.

![base](doc/base-s.jpg)



## Troubleshooting

- **Permission Issues**: Ensure udev rules are set correctly and you have the necessary permissions to access the device.

- **Build Errors**: Check that all dependencies are installed correctly. If errors persist, try cleaning the project with `cargo clean` and rebuild.



## LICENSE

This source code is licensed under MIT. Other Hardware Schematic documents are licensed under CC-BY-SA V4.0.



This project uses the following libraries and resources:

  

https://github.com/jlocash/esp-camera-rs



https://github.com/0015/ESP32-OV5640-AF



These libraries are licensed under each library's respective licenses.