Modify to adapt to the new version nncase and SDK

K210code/README.md

@@ -4,22 +4,24 @@ Make a directory named `ncc`. Download [nncase](<https://github.com/kendryte/nnc
 
 #### *pb* file to tflite
 
-Copy the pretrained model `mobilenetv1_1.0.pb` in `pretrained` directory to `ncc\bin`. 
+Copy the pretrained model `mobilenetv1_1.0.pb` in `pretrained` directory to `ncc/bin`. 
 
-Enter `ncc\bin` directory.
+Enter `ncc/bin` directory.
 
 ```shell
-./toco --input_file=mobilenetv1_1.0.pb --input_format=TENSORFLOW_GRAPHDEF --output_file=mobilenetv1_1.0.tflite --output_format=TFLITE --input_shape=1,224,224,3 --input_array=inputs --output_array=MobileNetV1/Bottleneck2/BatchNorm/Reshape_1 --inference=FLOAT
+toco --graph_def_file=mobilenetv1_1.0.pb --output_file=mobilenetv1_1.0.tflite --output_format=TFLITE --input_shape=1,224,224,3 --input_arrays=inputs --output_arrays=MobileNetV1/Bottleneck2/BatchNorm/Reshape_1 --inference_type=FLOAT
 ```
 
 #### tflite to kmodel
 
-Enter `ncc` directory and place the dataset into `ncc\dataset` directory.
+Enter `ncc` directory and place a few pictures of your dataset into `ncc/dataset` directory.
 
 ```shell
-./ncc -i tflite -o k210model --dataset ./dataset ./bin/mobilenetv1_1.0.tflite ./bin/mobilenetv1_1.0.kmodel
+./ncc compile ./bin/mobilenetv1_1.0.tflite ./bin/mobilenetv1_1.0.kmodel -i tflite -o kmodel --dataset ./dataset/
 ```
 
+**Note**: Pictures in `ncc/dataset` are used for quantization. They should cover all classes of your dataset.
+
 ### Prepare image for test
 
 Convert an image, for example `eagle.jpg`, to a C file.
@@ -39,6 +41,7 @@ with open('image.c','w') as f:
 
 ### Test
 
-Copy the `K210code` directory to `kendryte-standalone-sdk\src`. Build and download to KD233 to check the results.
+Copy the `K210code` directory to `kendryte-standalone-sdk/src`. Build and download to KD233 to check the results.
+
+**Note**: `develop` branch of `kendryte-standalone-sdk` is required.
 
-**Note**: `develop` branch of `kendryte-standalone-sdk` is required.

K210code/main.c

@@ -14,15 +14,18 @@
  */
 #include <stdio.h>
 #include <sysctl.h>
+#include <string.h>
 #include "uarths.h"
 #include "kpu.h"
 #include "incbin.h"
+#include "iomem.h"
+#include "syscalls.h"
 
-#define INCBIN_STYLE INCBIN_STYLE_SNAKE
+#define INCBIN_STYLE INCBIN_STYLE_SNAKE
 #define INCBIN_PREFIX
 
 #define PLL0_OUTPUT_FREQ 800000000UL
-#define PLL1_OUTPUT_FREQ 300000000UL
+#define PLL1_OUTPUT_FREQ 400000000UL
 
 INCBIN(model, "mobilenetv1_1.0.kmodel");
 
@@ -32,6 +35,9 @@ volatile uint32_t g_ai_done_flag;
 
 extern const unsigned char gImage_image[] __attribute__((aligned(128)));
 
+#define IMAGE_DATA_SIZE (224 * 224 * 3)
+uint8_t *pImage;
+
 static int ai_done(void *ctx)
 {
     g_ai_done_flag = 1;
@@ -48,9 +54,20 @@ int main()
     uarths_init();
     plic_init();
     
+    pImage = (uint8_t*)iomem_malloc(IMAGE_DATA_SIZE);
+    if (pImage)
+    {
+        memcpy(pImage, gImage_image, IMAGE_DATA_SIZE);
+    }
+    else
+    {
+        printf("Bad allocation!\n");
+        return 1;
+    }
+
     if (kpu_load_kmodel(&task, model_data) != 0)
-    {
+    {
-        printf("\nmodel init error\n");
+        printf("\nmodel init error\n");
         return -1;
     }
 
@@ -58,7 +75,7 @@ int main()
 
     printf("System Start\n");
     g_ai_done_flag = 0;
-    kpu_run_kmodel(&task, gImage_image, DMAC_CHANNEL5, ai_done, NULL);
+    kpu_run_kmodel(&task, pImage, DMAC_CHANNEL5, ai_done, NULL);
     while (g_ai_done_flag == 0);
     float *output;
     size_t output_size;