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!15106 fix DeepText 310 inference bug and fasterrcnn bug 

From: @yuzhenhua666
Reviewed-by: @c_34,@oacjiewen
Signed-off-by: @c_34
This commit is contained in:
mindspore-ci-bot 2021-04-14 09:23:46 +08:00 committed by Gitee
parent c2c20e8173 f3ccaed062
commit 97e3fc1d5c
2 changed files with 9 additions and 18 deletions
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2
model_zoo/official/cv/deeptext/postprocess.py
View File

@ -36,7 +36,7 @@ def get_pred(file, result_path):
all_bbox_file = os.path.join(result_path, file_name + "_0.bin")
all_label_file = os.path.join(result_path, file_name + "_1.bin")
all_mask_file = os.path.join(result_path, file_name + "_2.bin")
all_bbox = np.fromfile(all_bbox_file, dtype=np.float16).reshape(config.test_batch_size, 1000, 5)
all_bbox = np.fromfile(all_bbox_file, dtype=np.float32).reshape(config.test_batch_size, 1000, 5)
all_label = np.fromfile(all_label_file, dtype=np.int32).reshape(config.test_batch_size, 1000, 1)
all_mask = np.fromfile(all_mask_file, dtype=np.bool).reshape(config.test_batch_size, 1000, 1)

25
model_zoo/official/cv/faster_rcnn/ascend310_infer/src/AclProcess.cpp
View File

@ -23,7 +23,7 @@
* @attention context is passed in as a parameter after being created in ResourceManager::InitResource
*/
AclProcess::AclProcess(int deviceId, const std::string &om_path, uint32_t width, uint32_t height)
: deviceId_(deviceId), stream_(nullptr), modelProcess_(nullptr), dvppCommon_(nullptr), keepRatio_(false) {
: deviceId_(deviceId), stream_(nullptr), modelProcess_(nullptr), dvppCommon_(nullptr), keepRatio_(true) {
modelInfo_.modelPath = om_path;
modelInfo_.modelWidth = width;
modelInfo_.modelHeight = height;
@ -284,29 +284,22 @@ int AclProcess::ModelInfer(std::map<double, double> *costTime_map) {
heightScale = static_cast<float>(resizeOutData->height) / inputImg->height;
}
aclFloat16 inputWidth = aclFloatToFloat16(static_cast<float>(inputImg->width));
aclFloat16 inputHeight = aclFloatToFloat16(static_cast<float>(inputImg->height));
aclFloat16 resizeWidthRatioFp16 = aclFloatToFloat16(widthScale);
aclFloat16 resizeHeightRatioFp16 = aclFloatToFloat16(heightScale);
aclFloat16 *im_info = reinterpret_cast<aclFloat16 *>(malloc(sizeof(aclFloat16) * 4));
im_info[0] = inputHeight;
im_info[1] = inputWidth;
im_info[2] = resizeHeightRatioFp16;
im_info[3] = resizeWidthRatioFp16;
float im_info[4];
im_info[0] = static_cast<float>(inputImg->height);
im_info[1] = static_cast<float>(inputImg->width);
im_info[2] = heightScale;
im_info[3] = widthScale;
void *imInfo_dst = nullptr;
int ret = aclrtMalloc(&imInfo_dst, 8, ACL_MEM_MALLOC_NORMAL_ONLY);
int ret = aclrtMalloc(&imInfo_dst, 16, ACL_MEM_MALLOC_NORMAL_ONLY);
if (ret != ACL_ERROR_NONE) {
std::cout << "aclrtMalloc failed, ret = " << ret << std::endl;
aclrtFree(imInfo_dst);
free(im_info);
return ret;
}
ret = aclrtMemcpy(reinterpret_cast<uint8_t *>(imInfo_dst), 8, im_info, 8, ACL_MEMCPY_HOST_TO_DEVICE);
ret = aclrtMemcpy(reinterpret_cast<uint8_t *>(imInfo_dst), 16, im_info, 16, ACL_MEMCPY_HOST_TO_DEVICE);
if (ret != ACL_ERROR_NONE) {
std::cout << "aclrtMemcpy failed, ret = " << ret << std::endl;
aclrtFree(imInfo_dst);
free(im_info);
return ret;
}
@ -320,7 +313,6 @@ int AclProcess::ModelInfer(std::map<double, double> *costTime_map) {
ret = modelProcess_->ModelInference(inputBuffers, inputSizes, outputBuffers_, outputSizes_, costTime_map);
if (ret != OK) {
aclrtFree(imInfo_dst);
free(im_info);
std::cout << "Failed to execute the classification model, ret = " << ret << "." << std::endl;
return ret;
}
@ -330,7 +322,6 @@ int AclProcess::ModelInfer(std::map<double, double> *costTime_map) {
std::cout << "aclrtFree image info failed" << std::endl;
return ret;
}
free(im_info);
RELEASE_DVPP_DATA(resizeOutData->data);
return OK;
}