diff --git a/APP_Framework/Framework/knowing/Kconfig b/APP_Framework/Framework/knowing/Kconfig
index 94b8d9c43..c283404d3 100644
--- a/APP_Framework/Framework/knowing/Kconfig
+++ b/APP_Framework/Framework/knowing/Kconfig
@@ -3,5 +3,6 @@ menuconfig SUPPORT_KNOWING_FRAMEWORK
         default y
 
 if SUPPORT_KNOWING_FRAMEWORK
-        source "$APP_DIR/Framework/knowing/tensorflow-lite/Kconfig"        
+        source "$APP_DIR/Framework/knowing/tensorflow-lite/Kconfig"
+        source "$APP_DIR/Framework/knowing/kpu-postprocessing/Kconfig"
 endif
diff --git a/APP_Framework/Framework/knowing/kpu-postprocessing/Kconfig b/APP_Framework/Framework/knowing/kpu-postprocessing/Kconfig
new file mode 100644
index 000000000..73ec5548b
--- /dev/null
+++ b/APP_Framework/Framework/knowing/kpu-postprocessing/Kconfig
@@ -0,0 +1,5 @@
+menuconfig USING_KPU_POSTPROCESSING
+    bool "kpu model postprocessing"
+    default y
+
+source "$APP_DIR/Framework/knowing/kpu-postprocessing/yolov2/Kconfig"
\ No newline at end of file
diff --git a/APP_Framework/Framework/knowing/kpu-postprocessing/SConscript b/APP_Framework/Framework/knowing/kpu-postprocessing/SConscript
new file mode 100644
index 000000000..f307e3f70
--- /dev/null
+++ b/APP_Framework/Framework/knowing/kpu-postprocessing/SConscript
@@ -0,0 +1,14 @@
+import os
+Import('RTT_ROOT')
+from building import *
+
+cwd = GetCurrentDir()
+objs = []
+list = os.listdir(cwd)
+
+for d in list:
+    path = os.path.join(cwd, d)
+    if os.path.isfile(os.path.join(path, 'SConscript')):
+        objs = objs + SConscript(os.path.join(path, 'SConscript'))
+
+Return('objs')
diff --git a/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/Kconfig b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/Kconfig
new file mode 100644
index 000000000..3b7c11c7e
--- /dev/null
+++ b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/Kconfig
@@ -0,0 +1,7 @@
+menuconfig USING_YOLOV2
+    bool "yolov2 region layer"
+	depends on USING_KPU_POSTPROCESSING
+    default n
+
+
+
diff --git a/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/SConscript b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/SConscript
new file mode 100644
index 000000000..7328fce52
--- /dev/null
+++ b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/SConscript
@@ -0,0 +1,10 @@
+from building import *
+import os
+
+cwd = GetCurrentDir()
+
+src = Glob('*.c')
+
+group = DefineGroup('yolov2', src, depend = ['USING_YOLOV2'], CPPPATH = [cwd])
+
+Return('group')
diff --git a/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.c b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.c
new file mode 100644
index 000000000..6ca2182e8
--- /dev/null
+++ b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.c
@@ -0,0 +1,437 @@
+#include <stdlib.h>
+#include <math.h>
+#include <stdio.h>
+#include "region_layer.h"
+
+typedef struct
+{
+    float x;
+    float y;
+    float w;
+    float h;
+} box_t;
+
+typedef struct
+{
+    int index;
+    int class;
+    float **probs;
+} sortable_box_t;
+
+
+int region_layer_init(region_layer_t *rl, int width, int height, int channels, int origin_width, int origin_height)
+{
+    int flag = 0;
+
+    rl->coords = 4;
+    rl->image_width = 320;
+    rl->image_height = 240;
+
+    rl->classes = channels / 5 - 5;
+    rl->net_width = origin_width;
+    rl->net_height = origin_height;
+    rl->layer_width = width;
+    rl->layer_height = height;
+    rl->boxes_number = (rl->layer_width * rl->layer_height * rl->anchor_number); 
+    rl->output_number = (rl->boxes_number * (rl->classes + rl->coords + 1));
+
+    rl->output = malloc(rl->output_number * sizeof(float));
+    if (rl->output == NULL)
+    {
+        flag = -1;
+        goto malloc_error;
+    }
+    rl->boxes = malloc(rl->boxes_number * sizeof(box_t));
+    if (rl->boxes == NULL)
+    {
+        flag = -2;
+        goto malloc_error;
+    }
+    rl->probs_buf = malloc(rl->boxes_number * (rl->classes + 1) * sizeof(float));
+    if (rl->probs_buf == NULL)
+    {
+        flag = -3;
+        goto malloc_error;
+    }
+    rl->probs = malloc(rl->boxes_number * sizeof(float *));
+    if (rl->probs == NULL)
+    {
+        flag = -4;
+        goto malloc_error;
+    }
+    for (uint32_t i = 0; i < rl->boxes_number; i++)
+        rl->probs[i] = &(rl->probs_buf[i * (rl->classes + 1)]);
+    return 0;
+malloc_error:
+    free(rl->output);
+    free(rl->boxes);
+    free(rl->probs_buf);
+    free(rl->probs);
+    return flag;
+}
+
+void region_layer_deinit(region_layer_t *rl)
+{
+    free(rl->output);
+    free(rl->boxes);
+    free(rl->probs_buf);
+    free(rl->probs);
+}
+
+static inline float sigmoid(float x)
+{
+    return 1.f / (1.f + expf(-x));
+}
+
+static void activate_array(region_layer_t *rl, int index, int n)
+{
+    float *output = &rl->output[index];
+    float *input = &rl->input[index];
+
+    for (int i = 0; i < n; ++i)
+        output[i] = sigmoid(input[i]);
+}
+
+static int entry_index(region_layer_t *rl, int location, int entry)
+{
+    int wh = rl->layer_width * rl->layer_height;
+    int n   = location / wh;
+    int loc = location % wh;
+
+    return n * wh * (rl->coords + rl->classes + 1) + entry * wh + loc;
+}
+
+static void softmax(region_layer_t *rl, float *input, int n, int stride, float *output)
+{
+    int i;
+    float diff;
+    float e;
+    float sum = 0;
+    float largest_i = input[0];
+
+    for (i = 0; i < n; ++i)
+    {
+        if (input[i * stride] > largest_i)
+            largest_i = input[i * stride];
+    }
+
+    for (i = 0; i < n; ++i) {
+        diff = input[i * stride] - largest_i;
+        e = expf(diff);
+        sum += e;
+        output[i * stride] = e;
+    }
+    for (i = 0; i < n; ++i)
+        output[i * stride] /= sum;
+}
+
+static void softmax_cpu(region_layer_t *rl, float *input, int n, int batch, int batch_offset, int groups, int stride, float *output)
+{
+    int g, b;
+
+    for (b = 0; b < batch; ++b) {
+        for (g = 0; g < groups; ++g)
+            softmax(rl, input + b * batch_offset + g, n, stride, output + b * batch_offset + g);
+    }
+}
+
+static void forward_region_layer(region_layer_t *rl)
+{
+    int index;
+
+    for (index = 0; index < rl->output_number; index++)
+        rl->output[index] = rl->input[index];
+
+    for (int n = 0; n < rl->anchor_number; ++n)
+    {
+        index = entry_index(rl, n * rl->layer_width * rl->layer_height, 0);
+        activate_array(rl, index, 2 * rl->layer_width * rl->layer_height);
+        index = entry_index(rl, n * rl->layer_width * rl->layer_height, 4);
+        activate_array(rl, index, rl->layer_width * rl->layer_height);
+    }
+
+    index = entry_index(rl, 0, rl->coords + 1);
+    softmax_cpu(rl, rl->input + index, rl->classes, rl->anchor_number,
+            rl->output_number / rl->anchor_number, rl->layer_width * rl->layer_height,
+            rl->layer_width * rl->layer_height, rl->output + index);
+}
+
+static void correct_region_boxes(region_layer_t *rl, box_t *boxes)
+{
+    uint32_t net_width = rl->net_width;
+    uint32_t net_height = rl->net_height;
+    uint32_t image_width = rl->image_width;
+    uint32_t image_height = rl->image_height;
+    uint32_t boxes_number = rl->boxes_number;
+    int new_w = 0;
+    int new_h = 0;
+
+    if (((float)net_width / image_width) <
+        ((float)net_height / image_height)) {
+        new_w = net_width;
+        new_h = (image_height * net_width) / image_width;
+    } else {
+        new_h = net_height;
+        new_w = (image_width * net_height) / image_height;
+    }
+    for (int i = 0; i < boxes_number; ++i) {
+        box_t b = boxes[i];
+
+        b.x = (b.x - (net_width - new_w) / 2. / net_width) /
+              ((float)new_w / net_width);
+        b.y = (b.y - (net_height - new_h) / 2. / net_height) /
+              ((float)new_h / net_height);
+        b.w *= (float)net_width / new_w;
+        b.h *= (float)net_height / new_h;
+        boxes[i] = b;
+    }
+}
+
+static box_t get_region_box(float *x, float *biases, int n, int index, int i, int j, int w, int h, int stride)
+{
+    volatile box_t b;
+
+    b.x = (i + x[index + 0 * stride]) / w;
+    b.y = (j + x[index + 1 * stride]) / h;
+    b.w = expf(x[index + 2 * stride]) * biases[2 * n] / w;
+    b.h = expf(x[index + 3 * stride]) * biases[2 * n + 1] / h;
+    return b;
+}
+
+static void get_region_boxes(region_layer_t *rl, float *predictions, float **probs, box_t *boxes)
+{
+    uint32_t layer_width = rl->layer_width;
+    uint32_t layer_height = rl->layer_height;
+    uint32_t anchor_number = rl->anchor_number;
+    uint32_t classes = rl->classes;
+    uint32_t coords = rl->coords;
+    float threshold = rl->threshold;
+
+    for (int i = 0; i < layer_width * layer_height; ++i)
+    {
+        int row = i / layer_width;
+        int col = i % layer_width;
+
+        for (int n = 0; n < anchor_number; ++n)
+        {
+            int index = n * layer_width * layer_height + i;
+
+            for (int j = 0; j < classes; ++j)
+                probs[index][j] = 0;
+            int obj_index = entry_index(rl, n * layer_width * layer_height + i, coords);
+            int box_index = entry_index(rl, n * layer_width * layer_height + i, 0);
+            float scale  = predictions[obj_index];
+
+            boxes[index] = get_region_box(predictions, rl->anchor, n, box_index, col, row,
+                layer_width, layer_height, layer_width * layer_height);
+
+            float max = 0;
+
+            for (int j = 0; j < classes; ++j)
+            {
+                int class_index = entry_index(rl, n * layer_width * layer_height + i, coords + 1 + j);
+                float prob = scale * predictions[class_index];
+
+                probs[index][j] = (prob > threshold) ? prob : 0;
+                if (prob > max)
+                    max = prob;
+            }
+            probs[index][classes] = max;
+        }
+    }
+    correct_region_boxes(rl, boxes);
+}
+
+static int nms_comparator(void *pa, void *pb)
+{
+    sortable_box_t a = *(sortable_box_t *)pa;
+    sortable_box_t b = *(sortable_box_t *)pb;
+    float diff = a.probs[a.index][b.class] - b.probs[b.index][b.class];
+
+    if (diff < 0)
+        return 1;
+    else if (diff > 0)
+        return -1;
+    return 0;
+}
+
+static float overlap(float x1, float w1, float x2, float w2)
+{
+    float l1 = x1 - w1/2;
+    float l2 = x2 - w2/2;
+    float left = l1 > l2 ? l1 : l2;
+    float r1 = x1 + w1/2;
+    float r2 = x2 + w2/2;
+    float right = r1 < r2 ? r1 : r2;
+
+    return right - left;
+}
+
+static float box_intersection(box_t a, box_t b)
+{
+    float w = overlap(a.x, a.w, b.x, b.w);
+    float h = overlap(a.y, a.h, b.y, b.h);
+
+    if (w < 0 || h < 0)
+        return 0;
+    return w * h;
+}
+
+static float box_union(box_t a, box_t b)
+{
+    float i = box_intersection(a, b);
+    float u = a.w * a.h + b.w * b.h - i;
+
+    return u;
+}
+
+static float box_iou(box_t a, box_t b)
+{
+    return box_intersection(a, b) / box_union(a, b);
+}
+
+static void do_nms_sort(region_layer_t *rl, box_t *boxes, float **probs)
+{
+    uint32_t boxes_number = rl->boxes_number;
+    uint32_t classes = rl->classes;
+    float nms_value = rl->nms_value;
+    int i, j, k;
+    sortable_box_t s[boxes_number];
+
+    for (i = 0; i < boxes_number; ++i)
+    {
+        s[i].index = i;
+        s[i].class = 0;
+        s[i].probs = probs;
+    }
+
+    for (k = 0; k < classes; ++k)
+    {
+        for (i = 0; i < boxes_number; ++i)
+            s[i].class = k;
+        qsort(s, boxes_number, sizeof(sortable_box_t), nms_comparator);
+        for (i = 0; i < boxes_number; ++i)
+        {
+            if (probs[s[i].index][k] == 0)
+                continue;
+            box_t a = boxes[s[i].index];
+
+            for (j = i + 1; j < boxes_number; ++j)
+            {
+                box_t b = boxes[s[j].index];
+
+                if (box_iou(a, b) > nms_value)
+                    probs[s[j].index][k] = 0;
+            }
+        }
+    }
+}
+
+static int max_index(float *a, int n)
+{
+    int i, max_i = 0;
+    float max = a[0];
+
+    for (i = 1; i < n; ++i)
+    {
+        if (a[i] > max)
+        {
+            max   = a[i];
+            max_i = i;
+        }
+    }
+    return max_i;
+}
+
+static void region_layer_output(region_layer_t *rl, obj_info_t *obj_info)
+{
+    uint32_t obj_number = 0;
+    uint32_t image_width = rl->image_width;
+    uint32_t image_height = rl->image_height;
+    uint32_t boxes_number = rl->boxes_number;
+    float threshold = rl->threshold;
+    box_t *boxes = (box_t *)rl->boxes;
+    
+    for (int i = 0; i < rl->boxes_number; ++i)
+    {
+        int class  = max_index(rl->probs[i], rl->classes);
+        float prob = rl->probs[i][class];
+
+        if (prob > threshold)
+        {
+            box_t *b = boxes + i;
+            obj_info->obj[obj_number].x1 = b->x * image_width - (b->w * image_width / 2);
+            obj_info->obj[obj_number].y1 = b->y * image_height - (b->h * image_height / 2);
+            obj_info->obj[obj_number].x2 = b->x * image_width + (b->w * image_width / 2);
+            obj_info->obj[obj_number].y2 = b->y * image_height + (b->h * image_height / 2);
+            obj_info->obj[obj_number].class_id = class;
+            obj_info->obj[obj_number].prob = prob;
+            obj_number++;
+        }
+    }
+    obj_info->obj_number = obj_number;
+}
+
+void region_layer_run(region_layer_t *rl, obj_info_t *obj_info)
+{
+    forward_region_layer(rl);
+    get_region_boxes(rl, rl->output, rl->probs, rl->boxes);
+    do_nms_sort(rl, rl->boxes, rl->probs);
+    region_layer_output(rl, obj_info);
+}
+
+void draw_edge(uint32_t *gram, obj_info_t *obj_info, uint32_t index, uint16_t color)
+{
+    uint32_t data = ((uint32_t)color << 16) | (uint32_t)color;
+    uint32_t *addr1, *addr2, *addr3, *addr4, x1, y1, x2, y2;
+
+    x1 = obj_info->obj[index].x1;
+    y1 = obj_info->obj[index].y1;
+    x2 = obj_info->obj[index].x2;
+    y2 = obj_info->obj[index].y2;
+
+    if (x1 <= 0)
+        x1 = 1;
+    if (x2 >= 319)
+        x2 = 318;
+    if (y1 <= 0)
+        y1 = 1;
+    if (y2 >= 239)
+        y2 = 238;
+
+    addr1 = gram + (320 * y1 + x1) / 2;
+    addr2 = gram + (320 * y1 + x2 - 8) / 2;
+    addr3 = gram + (320 * (y2 - 1) + x1) / 2;
+    addr4 = gram + (320 * (y2 - 1) + x2 - 8) / 2;
+    for (uint32_t i = 0; i < 4; i++)
+    {
+        *addr1 = data;
+        *(addr1 + 160) = data;
+        *addr2 = data;
+        *(addr2 + 160) = data;
+        *addr3 = data;
+        *(addr3 + 160) = data;
+        *addr4 = data;
+        *(addr4 + 160) = data;
+        addr1++;
+        addr2++;
+        addr3++;
+        addr4++;
+    }
+    addr1 = gram + (320 * y1 + x1) / 2;
+    addr2 = gram + (320 * y1 + x2 - 2) / 2;
+    addr3 = gram + (320 * (y2 - 8) + x1) / 2;
+    addr4 = gram + (320 * (y2 - 8) + x2 - 2) / 2;
+    for (uint32_t i = 0; i < 8; i++)
+    {
+        *addr1 = data;
+        *addr2 = data;
+        *addr3 = data;
+        *addr4 = data;
+        addr1 += 160;
+        addr2 += 160;
+        addr3 += 160;
+        addr4 += 160;
+    }
+}
+
diff --git a/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.h b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.h
new file mode 100644
index 000000000..9b8a52197
--- /dev/null
+++ b/APP_Framework/Framework/knowing/kpu-postprocessing/yolov2/region_layer.h
@@ -0,0 +1,49 @@
+#ifndef _REGION_LAYER
+#define _REGION_LAYER
+
+#include <stdint.h>
+#include "kpu.h"
+
+typedef struct
+{
+    uint32_t obj_number;
+    struct
+    {
+        uint32_t x1;
+        uint32_t y1;
+        uint32_t x2;
+        uint32_t y2;
+        uint32_t class_id;
+        float prob;
+    } obj[10];
+} obj_info_t;
+
+typedef struct
+{
+    float threshold;
+    float nms_value;
+    uint32_t coords;
+    uint32_t anchor_number;
+    float *anchor;
+    uint32_t image_width;
+    uint32_t image_height;
+    uint32_t classes;
+    uint32_t net_width;
+    uint32_t net_height;
+    uint32_t layer_width;
+    uint32_t layer_height;
+    uint32_t boxes_number;
+    uint32_t output_number;
+    void *boxes;
+    float *input;
+    float *output;
+    float *probs_buf;
+    float **probs;
+} region_layer_t;
+
+int region_layer_init(region_layer_t *rl, int width, int height, int channels, int origin_width, int origin_height);
+void region_layer_deinit(region_layer_t *rl);
+void region_layer_run(region_layer_t *rl, obj_info_t *obj_info);
+void draw_edge(uint32_t *gram, obj_info_t *obj_info, uint32_t index, uint16_t color);
+
+#endif // _REGION_LAYER