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ipa: rpi: Add support for the Sony IMX500 camera sensor
Add a Sony IMX500 camera helper to the IPA. This also includes support for the on-chip CNN hardware accelerator and parsing of the neural network data stream returned in the metadata buffer. Add tuning files for both VC4 and PiSP platforms. Signed-off-by: Naushir Patuck <naush@raspberrypi.com>
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/* SPDX-License-Identifier: BSD-2-Clause */ | ||
/* | ||
* Copyright (C) 2024, Raspberry Pi Ltd | ||
* | ||
* cam_helper_imx500.cpp - camera helper for imx500 sensor | ||
*/ | ||
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#include <algorithm> | ||
#include <assert.h> | ||
#include <cmath> | ||
#include <fstream> | ||
#include <memory> | ||
#include <stddef.h> | ||
#include <stdio.h> | ||
#include <stdlib.h> | ||
#include <string.h> | ||
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#include <libcamera/base/log.h> | ||
#include <libcamera/base/span.h> | ||
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#include <libcamera/control_ids.h> | ||
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#include "imx500_tensor_parser/imx500_tensor_parser.h" | ||
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#include "cam_helper.h" | ||
#include "md_parser.h" | ||
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using namespace RPiController; | ||
using namespace libcamera; | ||
using libcamera::utils::Duration; | ||
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namespace libcamera { | ||
LOG_DECLARE_CATEGORY(IPARPI) | ||
} | ||
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/* | ||
* We care about two gain registers and a pair of exposure registers. Their | ||
* I2C addresses from the Sony IMX500 datasheet: | ||
*/ | ||
constexpr uint32_t expHiReg = 0x0202; | ||
constexpr uint32_t expLoReg = 0x0203; | ||
constexpr uint32_t gainHiReg = 0x0204; | ||
constexpr uint32_t gainLoReg = 0x0205; | ||
constexpr uint32_t frameLengthHiReg = 0x0340; | ||
constexpr uint32_t frameLengthLoReg = 0x0341; | ||
constexpr uint32_t lineLengthHiReg = 0x0342; | ||
constexpr uint32_t lineLengthLoReg = 0x0343; | ||
constexpr uint32_t temperatureReg = 0x013a; | ||
constexpr std::initializer_list<uint32_t> registerList = { expHiReg, expLoReg, gainHiReg, gainLoReg, frameLengthHiReg, frameLengthLoReg, | ||
lineLengthHiReg, lineLengthLoReg, temperatureReg }; | ||
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class CamHelperImx500 : public CamHelper | ||
{ | ||
public: | ||
CamHelperImx500(); | ||
uint32_t gainCode(double gain) const override; | ||
double gain(uint32_t gainCode) const override; | ||
void prepare(libcamera::Span<const uint8_t> buffer, Metadata &metadata) override; | ||
std::pair<uint32_t, uint32_t> getBlanking(Duration &exposure, Duration minFrameDuration, | ||
Duration maxFrameDuration) const override; | ||
void getDelays(int &exposureDelay, int &gainDelay, | ||
int &vblankDelay, int &hblankDelay) const override; | ||
bool sensorEmbeddedDataPresent() const override; | ||
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private: | ||
/* | ||
* Smallest difference between the frame length and integration time, | ||
* in units of lines. | ||
*/ | ||
static constexpr int frameIntegrationDiff = 22; | ||
/* Maximum frame length allowable for long exposure calculations. */ | ||
static constexpr int frameLengthMax = 0xffdc; | ||
/* Largest long exposure scale factor given as a left shift on the frame length. */ | ||
static constexpr int longExposureShiftMax = 7; | ||
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void parseInferenceData(libcamera::Span<const uint8_t> buffer, Metadata &metadata); | ||
void populateMetadata(const MdParser::RegisterMap ®isters, | ||
Metadata &metadata) const override; | ||
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std::unique_ptr<uint8_t[]> savedInputTensor_; | ||
}; | ||
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CamHelperImx500::CamHelperImx500() | ||
: CamHelper(std::make_unique<MdParserSmia>(registerList), frameIntegrationDiff) | ||
{ | ||
} | ||
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uint32_t CamHelperImx500::gainCode(double gain) const | ||
{ | ||
return static_cast<uint32_t>(1024 - 1024 / gain); | ||
} | ||
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double CamHelperImx500::gain(uint32_t gainCode) const | ||
{ | ||
return 1024.0 / (1024 - gainCode); | ||
} | ||
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void CamHelperImx500::prepare(libcamera::Span<const uint8_t> buffer, Metadata &metadata) | ||
{ | ||
MdParser::RegisterMap registers; | ||
DeviceStatus deviceStatus; | ||
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if (metadata.get("device.status", deviceStatus)) { | ||
LOG(IPARPI, Error) << "DeviceStatus not found from DelayedControls"; | ||
return; | ||
} | ||
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parseEmbeddedData(buffer, metadata); | ||
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/* | ||
* The DeviceStatus struct is first populated with values obtained from | ||
* DelayedControls. If this reports frame length is > frameLengthMax, | ||
* it means we are using a long exposure mode. Since the long exposure | ||
* scale factor is not returned back through embedded data, we must rely | ||
* on the existing exposure lines and frame length values returned by | ||
* DelayedControls. | ||
* | ||
* Otherwise, all values are updated with what is reported in the | ||
* embedded data. | ||
*/ | ||
if (deviceStatus.frameLength > frameLengthMax) { | ||
DeviceStatus parsedDeviceStatus; | ||
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metadata.get("device.status", parsedDeviceStatus); | ||
parsedDeviceStatus.shutterSpeed = deviceStatus.shutterSpeed; | ||
parsedDeviceStatus.frameLength = deviceStatus.frameLength; | ||
metadata.set("device.status", parsedDeviceStatus); | ||
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LOG(IPARPI, Debug) << "Metadata updated for long exposure: " | ||
<< parsedDeviceStatus; | ||
} | ||
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parseInferenceData(buffer, metadata); | ||
} | ||
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std::pair<uint32_t, uint32_t> CamHelperImx500::getBlanking(Duration &exposure, | ||
Duration minFrameDuration, | ||
Duration maxFrameDuration) const | ||
{ | ||
uint32_t frameLength, exposureLines; | ||
unsigned int shift = 0; | ||
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auto [vblank, hblank] = CamHelper::getBlanking(exposure, minFrameDuration, | ||
maxFrameDuration); | ||
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frameLength = mode_.height + vblank; | ||
Duration lineLength = hblankToLineLength(hblank); | ||
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/* | ||
* Check if the frame length calculated needs to be setup for long | ||
* exposure mode. This will require us to use a long exposure scale | ||
* factor provided by a shift operation in the sensor. | ||
*/ | ||
while (frameLength > frameLengthMax) { | ||
if (++shift > longExposureShiftMax) { | ||
shift = longExposureShiftMax; | ||
frameLength = frameLengthMax; | ||
break; | ||
} | ||
frameLength >>= 1; | ||
} | ||
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if (shift) { | ||
/* Account for any rounding in the scaled frame length value. */ | ||
frameLength <<= shift; | ||
exposureLines = CamHelperImx500::exposureLines(exposure, lineLength); | ||
exposureLines = std::min(exposureLines, frameLength - frameIntegrationDiff); | ||
exposure = CamHelperImx500::exposure(exposureLines, lineLength); | ||
} | ||
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return { frameLength - mode_.height, hblank }; | ||
} | ||
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void CamHelperImx500::getDelays(int &exposureDelay, int &gainDelay, | ||
int &vblankDelay, int &hblankDelay) const | ||
{ | ||
exposureDelay = 2; | ||
gainDelay = 2; | ||
vblankDelay = 3; | ||
hblankDelay = 3; | ||
} | ||
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bool CamHelperImx500::sensorEmbeddedDataPresent() const | ||
{ | ||
return true; | ||
} | ||
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void CamHelperImx500::parseInferenceData(libcamera::Span<const uint8_t> buffer, | ||
Metadata &metadata) | ||
{ | ||
/* Inference data comes after 2 lines of embedded data. */ | ||
constexpr unsigned int StartLine = 2; | ||
size_t bytesPerLine = (mode_.width * mode_.bitdepth) >> 3; | ||
if (hwConfig_.cfeDataBufferStrided) | ||
bytesPerLine = (bytesPerLine + 15) & ~15; | ||
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if (buffer.size() <= StartLine * bytesPerLine) | ||
return; | ||
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/* Check if an input tensor is needed - this is sticky! */ | ||
bool enableInputTensor = false; | ||
metadata.get("cnn.enable_input_tensor", enableInputTensor); | ||
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/* Cache the DNN metadata for fast parsing. */ | ||
unsigned int tensorBufferSize = buffer.size() - (StartLine * bytesPerLine); | ||
std::unique_ptr<uint8_t[]> cache = std::make_unique<uint8_t[]>(tensorBufferSize); | ||
memcpy(cache.get(), buffer.data() + StartLine * bytesPerLine, tensorBufferSize); | ||
Span<const uint8_t> tensors(cache.get(), tensorBufferSize); | ||
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std::unordered_map<TensorType, IMX500Tensors> offsets = RPiController::imx500SplitTensors(tensors); | ||
auto itIn = offsets.find(TensorType::InputTensor); | ||
auto itOut = offsets.find(TensorType::OutputTensor); | ||
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if (itIn != offsets.end() && itOut != offsets.end()) { | ||
const unsigned int inputTensorOffset = itIn->second.offset; | ||
const unsigned int outputTensorOffset = itOut->second.offset; | ||
const unsigned int inputTensorSize = outputTensorOffset - inputTensorOffset; | ||
Span<const uint8_t> inputTensor; | ||
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if (itIn->second.valid) { | ||
if (itOut->second.valid) { | ||
/* Valid input and output tensor, get the span directly from the current cache. */ | ||
inputTensor = Span<const uint8_t>(cache.get() + inputTensorOffset, | ||
inputTensorSize); | ||
} else { | ||
/* | ||
* Invalid output tensor with valid input tensor. | ||
* This is likely because the DNN takes longer than | ||
* a frame time to generate the output tensor. | ||
* | ||
* In such cases, we don't process the input tensor, | ||
* but simply save it for when the next output | ||
* tensor is valid. This way, we ensure that both | ||
* valid input and output tensors are in lock-step. | ||
*/ | ||
savedInputTensor_ = std::make_unique<uint8_t[]>(inputTensorSize); | ||
memcpy(savedInputTensor_.get(), cache.get() + inputTensorOffset, | ||
inputTensorSize); | ||
} | ||
} else if (itOut->second.valid && savedInputTensor_) { | ||
/* | ||
* Invalid input tensor with valid output tensor. This is | ||
* likely because the DNN takes longer than a frame time | ||
* to generate the output tensor. | ||
* | ||
* In such cases, use the previously saved input tensor | ||
* if possible. | ||
*/ | ||
inputTensor = Span<const uint8_t>(savedInputTensor_.get(), inputTensorSize); | ||
} | ||
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if (inputTensor.size()) { | ||
IMX500InputTensorInfo inputTensorInfo; | ||
if (!imx500ParseInputTensor(inputTensorInfo, inputTensor)) { | ||
CnnInputTensorInfo exported{}; | ||
exported.width = inputTensorInfo.width; | ||
exported.height = inputTensorInfo.height; | ||
exported.numChannels = inputTensorInfo.channels; | ||
strncpy(exported.networkName, inputTensorInfo.networkName.c_str(), | ||
sizeof(exported.networkName)); | ||
exported.networkName[sizeof(exported.networkName) - 1] = '\0'; | ||
metadata.set("cnn.input_tensor_info", exported); | ||
metadata.set("cnn.input_tensor", std::move(inputTensorInfo.data)); | ||
metadata.set("cnn.input_tensor_size", inputTensorInfo.size); | ||
} | ||
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/* We can now safely clear the saved input tensor. */ | ||
savedInputTensor_.reset(); | ||
} | ||
} | ||
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if (itOut != offsets.end() && itOut->second.valid) { | ||
unsigned int outputTensorOffset = itOut->second.offset; | ||
Span<const uint8_t> outputTensor(cache.get() + outputTensorOffset, | ||
tensorBufferSize - outputTensorOffset); | ||
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IMX500OutputTensorInfo outputTensorInfo; | ||
if (!imx500ParseOutputTensor(outputTensorInfo, outputTensor)) { | ||
CnnOutputTensorInfo exported{}; | ||
if (outputTensorInfo.numTensors < MaxNumTensors) { | ||
exported.numTensors = outputTensorInfo.numTensors; | ||
for (unsigned int i = 0; i < exported.numTensors; i++) { | ||
exported.info[i].tensorDataNum = outputTensorInfo.tensorDataNum[i]; | ||
exported.info[i].numDimensions = outputTensorInfo.numDimensions[i]; | ||
for (unsigned int j = 0; j < exported.info[i].numDimensions; j++) | ||
exported.info[i].size[j] = outputTensorInfo.vecDim[i][j].size; | ||
} | ||
} else { | ||
LOG(IPARPI, Debug) | ||
<< "IMX500 output tensor info export failed, numTensors > MaxNumTensors"; | ||
} | ||
strncpy(exported.networkName, outputTensorInfo.networkName.c_str(), | ||
sizeof(exported.networkName)); | ||
exported.networkName[sizeof(exported.networkName) - 1] = '\0'; | ||
metadata.set("cnn.output_tensor_info", exported); | ||
metadata.set("cnn.output_tensor", std::move(outputTensorInfo.data)); | ||
metadata.set("cnn.output_tensor_size", outputTensorInfo.totalSize); | ||
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auto itKpi = offsets.find(TensorType::Kpi); | ||
if (itKpi != offsets.end()) { | ||
constexpr unsigned int DnnRuntimeOffset = 9; | ||
constexpr unsigned int DspRuntimeOffset = 10; | ||
CnnKpiInfo kpi; | ||
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uint8_t *k = cache.get() + itKpi->second.offset; | ||
kpi.dnnRuntime = k[4 * DnnRuntimeOffset + 3] << 24 | | ||
k[4 * DnnRuntimeOffset + 2] << 16 | | ||
k[4 * DnnRuntimeOffset + 1] << 8 | | ||
k[4 * DnnRuntimeOffset]; | ||
kpi.dspRuntime = k[4 * DspRuntimeOffset + 3] << 24 | | ||
k[4 * DspRuntimeOffset + 2] << 16 | | ||
k[4 * DspRuntimeOffset + 1] << 8 | | ||
k[4 * DspRuntimeOffset]; | ||
metadata.set("cnn.kpi_info", kpi); | ||
} | ||
} | ||
} | ||
} | ||
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void CamHelperImx500::populateMetadata(const MdParser::RegisterMap ®isters, | ||
Metadata &metadata) const | ||
{ | ||
DeviceStatus deviceStatus; | ||
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deviceStatus.lineLength = lineLengthPckToDuration(registers.at(lineLengthHiReg) * 256 + | ||
registers.at(lineLengthLoReg)); | ||
deviceStatus.shutterSpeed = exposure(registers.at(expHiReg) * 256 + registers.at(expLoReg), | ||
deviceStatus.lineLength); | ||
deviceStatus.analogueGain = gain(registers.at(gainHiReg) * 256 + registers.at(gainLoReg)); | ||
deviceStatus.frameLength = registers.at(frameLengthHiReg) * 256 + registers.at(frameLengthLoReg); | ||
deviceStatus.sensorTemperature = std::clamp<int8_t>(registers.at(temperatureReg), -20, 80); | ||
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metadata.set("device.status", deviceStatus); | ||
} | ||
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static CamHelper *create() | ||
{ | ||
return new CamHelperImx500(); | ||
} | ||
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static RegisterCamHelper reg_imx500("imx500", &create); |
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