LC-OpenMv4 Smart Camera Image Processing Color Recognition Face Hunt Visual Inspection Line Module Development Board

Feature: 1. STM32H743VI ARM Cortex M7 processor, 216Mhz, 512KB RAM, 2MB flash. All I/O pins are 3.3V and 5V compatible. This processor has the following IO interface 2. Full speed USB interface, connected to the computer. When inserting the OpenMV camera monkey, your computer will appear with a virtual COM port to drink a USB flash drive. 3. The SD card slot has 100Mbs read and write, which allows your OpenMW camera to record video and extract machine vision material from the SD card. 4. An SPI bus speed of up to 54Mbs allows you to simply transfer image stream data to the LCD expansion board, WIFI expansion board, or another controller 5. An I2C bus, CAN bus, and an asynchronous serial bus (TX/RX) for connecting other controllers or sensors 6. A 12 bit ADC and a 12 bit DAC 7. 3 I/O pins for servo control 8. All IO ports can be used for interrupts and PWM 9. OV7725 sensor can process 640*480 8 bit grayscale image or 320*240 16 bit RGB565 color image under 80FPS Application: What the Open MV camera can do now (more in the future): Frame Differencing You can use the frame difference algorithm on the OpenMV Cam to see the motion in the scene. The frame difference algorithm can use OpenMV for security applications. 2. Color Tracking You can use OpenMV to detect up to 16 colors at a time in an image (actually never want to find more than 4 colors) and each color can have any number of different spots. OpenMV will tell you the location, size, center and direction of each blob. With color tracking, your OpenMV Cam can be programmed to track sun, line tracking, target tracking and more. 3. Marker Tracking You can use OpenMV Cam to detect the color of a color group instead of a separate color. This allows you to place color labels (labels of 2 or more colors) on the object, and OpenMV will get the contents of the label object. 4. Face Detection You can detect faces using OpenMV Cam (or any generic object). Your OpenMV camera can handle Haar templates for common object detection and comes with built-in Frontal Face templates and Eye Haar templates for detecting faces and eyes. 5. Eye Tracking You can use eye tracking to detect someone's gaze direction. You can use it to control the robot. Eye tracking detects the position of the pupil while detecting if there is an eye in the image. 6. Optical Flow You can use the optical flow to detect the picture in front of your OpenMV camera. For example, you can use the stability of the position of the light flow on the quadrotor in the air. 7. QR Code Detection/Decoding You can use the OpenMV Cam to read the QR code in its field of view. With QR code detection/decoding, you can enable intelligent robots to read labels in the environment. 8. Data Matrix Detection/Decoding The OpenMV Cam M7 can also detect and decode matrix codes (2D barcodes). 9. Linear Barcode Decoding The OpenMV Cam H7 can also handle 1D barcodes. He can decode EAN2, EAN5, EAN8, UPCE, ISBN10, UPCA, EAN13, ISBN13, I25, DATABAR, DARABAR_EXP, CODABAR, CODE39, CODE93, and CODE128. 10. AprilTag Tracking Even better than the QR code above, the OpenMV Cam M7 can also track up to 160x120 AprilTags, up to about 12FPS. AprilTags are the most advanced datum markers with constant rotation, constant scale, constant shear and constant illumination. 11. Line Detection OpenMV Cam can quickly complete infinitely long line detection with almost full frame rate. Moreover, you can also find segments that are not infinitely long. 12. Template Matching You can use OpenMV template matching to detect if there are similar images in the field of view. For example, you can use template matching to find markers on a PCB or to read known numbers on a display. 13. Image Capture You can use OpenMV to capture up to 320x240 RGB565 (or 640x480 grayscale) BMP / JPG / PPM / PGM images. You can control how images are captured directly in a Python script. Most importantly, using machine vision algorithms, draw lines, draw characters, and save. 14. Video Recording You can record up to 320x240 RGB565 (or 640x480 grayscale) MJPEG video or GIF images using OpenMV cameras. You can directly control how each video frame is recorded in a Python script and have full control over the beginning and end of the video recording. And, like taking an image, you can use machine vision algorithms to draw lines, draw characters, and save. Finally, all of the above features can be mixed with IO pin controls to match your own custom applications to talk to the real world. The 2.8mm focal length lens is on a standard M12 lens mount. If you want to use more custom lenses, you can install them easily. Sepecification: Processor ARM 32-bit Cortex-M7 CPU w/ Double Precision FPU 216 MHz (462 DMIPS) Core Mark Score: 1082 (compare w/ Raspberry Pi Zero: 2060) RAM Layout 128KB .DATA/.BSS/Heap/Stack 384KB Frame Buffer/Stack (512KB Total) Flash Layout 32KB Bootloader 96KB Embedded Flash Drive 1920KB Firmware (2MB Total) Supported image formats Grayscale, RGB565, JPEG Maximum supported pixels Grayscale: 640x480 and under RGB565: 320x240 and under Grayscale JPEG: 640x480 and under RGB565 JPEG: 640x480 and under Lens information Focal Length: 2.8mm Aperture: F2.0 Format: 1/3" Angle (Field-of-View): 115 Mount: M12*0.5 IR Cut Filter: 650nm (removable) Electrical information All pins are 5V tolerant with 3.3V output. All pins can sink or source up to 25mA. P6 is not 5V tolerant in ADC or DAC mode. Up to 120mA may be sinked or sourced in total between all pins. VIN may be between 3.6V and 5V. Do not draw more than 250mA from your OpenMV Cam's 3.3V rail. Weight 16g Size 45 x 36 x 30mm Power consumption Idle - no SD card: 90mA@3.3V Run - no SD card: 140mA@3.3V Idle - no SD card: 90mA@3.3V Run - no SD card: 150mA@3.3V Temperature range Sstorage -40C to 125C Run -20C to 70C Package includes: 1 x Camera module