Update image-clasification with explicit preprocessing.

ARM-software · Jun 14, 2019 · ecec350 · ecec350
1 parent 51a9f17
commit ecec350
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Showing 2 changed files with 28 additions and 18 deletions.
diff --git a/program/image-classification-armnn-tflite/.cm/meta.json b/program/image-classification-armnn-tflite/.cm/meta.json
@@ -78,11 +78,14 @@
  "script_name": "postprocess"
  },
  "pre_process_via_ck": {
- "data_uoa": "b98ee24399ef4c3a",
- "module_uoa": "script",
- "script_name": "preprocess"
+ "data_uoa":  "b98ee24399ef4c3a",
+ "module_uoa":  "script",
+ "script_name":  "schindler"
  },
  "run_cmd_main": "$#BIN_FILE#$",
+ "run_input_files": [
+ "$<<CK_ENV_TENSORFLOW_MODEL_TFLITE_FILEPATH>>$"
+ ],
  "run_output_files": [
  "tmp-ck-timer.json"
  ]
@@ -97,12 +100,12 @@
  "sort": 10,
  "tags": "dataset,imagenet,aux"
  },
- "imagenet-val": {
+ "images": {
  "force_target_as_host": "yes",
  "local": "yes",
- "name": "ImageNet dataset (val)",
+ "name": "ImageNet dataset (preprocessed subset)",
  "sort": 20,
- "tags": "dataset,imagenet,raw,val"
+ "tags": "dataset,imagenet,preprocessed"
  },
  "lib-python-numpy": {
  "local": "yes",
@@ -145,9 +148,11 @@
  "CK_RECREATE_CACHE": "NO",
  "CK_SKIP_IMAGES": 0,
  "CK_SUBTRACT_MEAN": "YES",
+ "CK_RESULTS_DIR": "predictions",
  "CK_TMP_IMAGE_SIZE": 0,
  "USE_NEON": "NO",
- "USE_OPENCL": "NO"
+ "USE_OPENCL": "NO",
+ "CK_SILENT_MODE": 0
  },
  "skip_bin_ext": "yes",
  "source_files": [

diff --git a/program/image-classification-armnn-tflite/benchmark.h b/program/image-classification-armnn-tflite/benchmark.h
@@ -108,19 +108,24 @@ class Accumulator {
 
 class BenchmarkSettings {
 public:
- const std::string graph_file = getenv_s("RUN_OPT_GRAPH_FILE");
- const std::string images_dir = getenv_s("RUN_OPT_IMAGE_DIR");
- const std::string images_file = getenv_s("RUN_OPT_IMAGE_LIST");
- const std::string result_dir = getenv_s("RUN_OPT_RESULT_DIR");
- const std::string data_layout = getenv_s("RUN_OPT_DATA_LAYOUT");
- const int batch_count = getenv_i("RUN_OPT_BATCH_COUNT");
- const int batch_size = getenv_i("RUN_OPT_BATCH_SIZE");
- const int image_size = getenv_i("RUN_OPT_IMAGE_SIZE");
+
+ const std::string images_dir = getenv_s("CK_ENV_DATASET_IMAGENET_PREPROCESSED_DIR");
+ const std::string images_file = getenv_s("CK_ENV_DATASET_IMAGENET_PREPROCESSED_SUBSET_FOF");
+ const std::string result_dir = getenv_s("CK_RESULTS_DIR");
+ const std::string input_layer_name = getenv_s("CK_ENV_TENSORFLOW_MODEL_INPUT_LAYER_NAME");
+ const std::string output_layer_name = getenv_s("CK_ENV_TENSORFLOW_MODEL_OUTPUT_LAYER_NAME");
+ const int batch_count = getenv_i("CK_BATCH_COUNT");
+ const int batch_size = getenv_i("CK_BATCH_SIZE");
+ const int image_size = getenv_i("CK_ENV_DATASET_IMAGENET_PREPROCESSED_INPUT_SQUARE_SIDE");
  const int num_channels = 3;
  const int num_classes = 1000;
- const bool normalize_img = getenv_i("RUN_OPT_NORMALIZE_DATA") != 0;
- const bool subtract_mean = getenv_i("RUN_OPT_SUBTRACT_MEAN") != 0;
- const bool full_report = getenv_i("RUN_OPT_SILENT_MODE") == 0;
+ const bool normalize_img = getenv_s("CK_ENV_TENSORFLOW_MODEL_NORMALIZE_DATA") == "YES";
+ const bool subtract_mean = getenv_s("CK_ENV_TENSORFLOW_MODEL_SUBTRACT_MEAN") == "YES";
+ const bool full_report = getenv_i("CK_SILENT_MODE") == 0;
+
+ const std::string graph_file = getenv_s("CK_ENV_TENSORFLOW_MODEL_TFLITE_FILEPATH");
+ const std::string data_layout = getenv_s("ML_MODEL_DATA_LAYOUT");
+
 
  BenchmarkSettings() {
  // Print settings