From 168af40fe9a3cc81c6ee16b3e81f154780c36bdb Mon Sep 17 00:00:00 2001
From: Scheaven <xuepengqiang>
Date: 星期四, 03 六月 2021 15:03:27 +0800
Subject: [PATCH] up new v4
---
lib/detecter_tools/darknet/crop_layer.c | 206 +++++++++++++++++++++++++-------------------------
1 files changed, 103 insertions(+), 103 deletions(-)
diff --git a/lib/detecter_tools/darknet/crop_layer.c b/lib/detecter_tools/darknet/crop_layer.c
index 9a7e22e..2d1fafc 100644
--- a/lib/detecter_tools/darknet/crop_layer.c
+++ b/lib/detecter_tools/darknet/crop_layer.c
@@ -1,103 +1,103 @@
-#include "utils.h"
-#include "crop_layer.h"
-#include "dark_cuda.h"
-#include <stdio.h>
-
-image get_crop_image(crop_layer l)
-{
- int h = l.out_h;
- int w = l.out_w;
- int c = l.out_c;
- return float_to_image(w,h,c,l.output);
-}
-
-void backward_crop_layer(const crop_layer l, network_state state){}
-void backward_crop_layer_gpu(const crop_layer l, network_state state){}
-
-crop_layer make_crop_layer(int batch, int h, int w, int c, int crop_height, int crop_width, int flip, float angle, float saturation, float exposure)
-{
- fprintf(stderr, "Crop Layer: %d x %d -> %d x %d x %d image\n", h,w,crop_height,crop_width,c);
- crop_layer l = { (LAYER_TYPE)0 };
- l.type = CROP;
- l.batch = batch;
- l.h = h;
- l.w = w;
- l.c = c;
- l.scale = (float)crop_height / h;
- l.flip = flip;
- l.angle = angle;
- l.saturation = saturation;
- l.exposure = exposure;
- l.out_w = crop_width;
- l.out_h = crop_height;
- l.out_c = c;
- l.inputs = l.w * l.h * l.c;
- l.outputs = l.out_w * l.out_h * l.out_c;
- l.output = (float*)xcalloc(l.outputs * batch, sizeof(float));
- l.forward = forward_crop_layer;
- l.backward = backward_crop_layer;
-
- #ifdef GPU
- l.forward_gpu = forward_crop_layer_gpu;
- l.backward_gpu = backward_crop_layer_gpu;
- l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
- l.rand_gpu = cuda_make_array(0, l.batch*8);
- #endif
- return l;
-}
-
-void resize_crop_layer(layer *l, int w, int h)
-{
- l->w = w;
- l->h = h;
-
- l->out_w = l->scale*w;
- l->out_h = l->scale*h;
-
- l->inputs = l->w * l->h * l->c;
- l->outputs = l->out_h * l->out_w * l->out_c;
-
- l->output = (float*)xrealloc(l->output, l->batch * l->outputs * sizeof(float));
- #ifdef GPU
- cuda_free(l->output_gpu);
- l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
- #endif
-}
-
-
-void forward_crop_layer(const crop_layer l, network_state state)
-{
- int i,j,c,b,row,col;
- int index;
- int count = 0;
- int flip = (l.flip && rand()%2);
- int dh = rand()%(l.h - l.out_h + 1);
- int dw = rand()%(l.w - l.out_w + 1);
- float scale = 2;
- float trans = -1;
- if(l.noadjust){
- scale = 1;
- trans = 0;
- }
- if(!state.train){
- flip = 0;
- dh = (l.h - l.out_h)/2;
- dw = (l.w - l.out_w)/2;
- }
- for(b = 0; b < l.batch; ++b){
- for(c = 0; c < l.c; ++c){
- for(i = 0; i < l.out_h; ++i){
- for(j = 0; j < l.out_w; ++j){
- if(flip){
- col = l.w - dw - j - 1;
- }else{
- col = j + dw;
- }
- row = i + dh;
- index = col+l.w*(row+l.h*(c + l.c*b));
- l.output[count++] = state.input[index]*scale + trans;
- }
- }
- }
- }
-}
+#include "utils.h"
+#include "crop_layer.h"
+#include "dark_cuda.h"
+#include <stdio.h>
+
+image get_crop_image(crop_layer l)
+{
+ int h = l.out_h;
+ int w = l.out_w;
+ int c = l.out_c;
+ return float_to_image(w,h,c,l.output);
+}
+
+void backward_crop_layer(const crop_layer l, network_state state){}
+void backward_crop_layer_gpu(const crop_layer l, network_state state){}
+
+crop_layer make_crop_layer(int batch, int h, int w, int c, int crop_height, int crop_width, int flip, float angle, float saturation, float exposure)
+{
+ fprintf(stderr, "Crop Layer: %d x %d -> %d x %d x %d image\n", h,w,crop_height,crop_width,c);
+ crop_layer l = { (LAYER_TYPE)0 };
+ l.type = CROP;
+ l.batch = batch;
+ l.h = h;
+ l.w = w;
+ l.c = c;
+ l.scale = (float)crop_height / h;
+ l.flip = flip;
+ l.angle = angle;
+ l.saturation = saturation;
+ l.exposure = exposure;
+ l.out_w = crop_width;
+ l.out_h = crop_height;
+ l.out_c = c;
+ l.inputs = l.w * l.h * l.c;
+ l.outputs = l.out_w * l.out_h * l.out_c;
+ l.output = (float*)xcalloc(l.outputs * batch, sizeof(float));
+ l.forward = forward_crop_layer;
+ l.backward = backward_crop_layer;
+
+ #ifdef GPU
+ l.forward_gpu = forward_crop_layer_gpu;
+ l.backward_gpu = backward_crop_layer_gpu;
+ l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
+ l.rand_gpu = cuda_make_array(0, l.batch*8);
+ #endif
+ return l;
+}
+
+void resize_crop_layer(layer *l, int w, int h)
+{
+ l->w = w;
+ l->h = h;
+
+ l->out_w = l->scale*w;
+ l->out_h = l->scale*h;
+
+ l->inputs = l->w * l->h * l->c;
+ l->outputs = l->out_h * l->out_w * l->out_c;
+
+ l->output = (float*)xrealloc(l->output, l->batch * l->outputs * sizeof(float));
+ #ifdef GPU
+ cuda_free(l->output_gpu);
+ l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
+ #endif
+}
+
+
+void forward_crop_layer(const crop_layer l, network_state state)
+{
+ int i,j,c,b,row,col;
+ int index;
+ int count = 0;
+ int flip = (l.flip && rand()%2);
+ int dh = rand()%(l.h - l.out_h + 1);
+ int dw = rand()%(l.w - l.out_w + 1);
+ float scale = 2;
+ float trans = -1;
+ if(l.noadjust){
+ scale = 1;
+ trans = 0;
+ }
+ if(!state.train){
+ flip = 0;
+ dh = (l.h - l.out_h)/2;
+ dw = (l.w - l.out_w)/2;
+ }
+ for(b = 0; b < l.batch; ++b){
+ for(c = 0; c < l.c; ++c){
+ for(i = 0; i < l.out_h; ++i){
+ for(j = 0; j < l.out_w; ++j){
+ if(flip){
+ col = l.w - dw - j - 1;
+ }else{
+ col = j + dw;
+ }
+ row = i + dh;
+ index = col+l.w*(row+l.h*(c + l.c*b));
+ l.output[count++] = state.input[index]*scale + trans;
+ }
+ }
+ }
+ }
+}
--
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