From a720bf74e233c956e5281871ede722a2c7cf54db Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Mon, 21 May 2018 21:15:04 +0000
Subject: [PATCH] Added flag -ext_output for detector demo. Fixed proportional resize of network for random=1
---
src/parser.c | 183 +++++++++++++++++++++++++++++++++++++++------
1 files changed, 158 insertions(+), 25 deletions(-)
diff --git a/src/parser.c b/src/parser.c
index cde06b4..2b013de 100644
--- a/src/parser.c
+++ b/src/parser.c
@@ -24,11 +24,15 @@
#include "parser.h"
#include "region_layer.h"
#include "reorg_layer.h"
+#include "reorg_old_layer.h"
#include "rnn_layer.h"
#include "route_layer.h"
#include "shortcut_layer.h"
#include "softmax_layer.h"
#include "utils.h"
+#include "upsample_layer.h"
+#include "yolo_layer.h"
+#include <stdint.h>
typedef struct{
char *type;
@@ -45,6 +49,7 @@
if (strcmp(type, "[cost]")==0) return COST;
if (strcmp(type, "[detection]")==0) return DETECTION;
if (strcmp(type, "[region]")==0) return REGION;
+ if (strcmp(type, "[yolo]") == 0) return YOLO;
if (strcmp(type, "[local]")==0) return LOCAL;
if (strcmp(type, "[conv]")==0
|| strcmp(type, "[convolutional]")==0) return CONVOLUTIONAL;
@@ -59,6 +64,7 @@
if (strcmp(type, "[max]")==0
|| strcmp(type, "[maxpool]")==0) return MAXPOOL;
if (strcmp(type, "[reorg]")==0) return REORG;
+ if (strcmp(type, "[reorg_old]") == 0) return REORG_OLD;
if (strcmp(type, "[avg]")==0
|| strcmp(type, "[avgpool]")==0) return AVGPOOL;
if (strcmp(type, "[dropout]")==0) return DROPOUT;
@@ -68,6 +74,7 @@
if (strcmp(type, "[soft]")==0
|| strcmp(type, "[softmax]")==0) return SOFTMAX;
if (strcmp(type, "[route]")==0) return ROUTE;
+ if (strcmp(type, "[upsample]") == 0) return UPSAMPLE;
return BLANK;
}
@@ -232,23 +239,83 @@
return layer;
}
+int *parse_yolo_mask(char *a, int *num)
+{
+ int *mask = 0;
+ if (a) {
+ int len = strlen(a);
+ int n = 1;
+ int i;
+ for (i = 0; i < len; ++i) {
+ if (a[i] == ',') ++n;
+ }
+ mask = calloc(n, sizeof(int));
+ for (i = 0; i < n; ++i) {
+ int val = atoi(a);
+ mask[i] = val;
+ a = strchr(a, ',') + 1;
+ }
+ *num = n;
+ }
+ return mask;
+}
+
+layer parse_yolo(list *options, size_params params)
+{
+ int classes = option_find_int(options, "classes", 20);
+ int total = option_find_int(options, "num", 1);
+ int num = total;
+
+ char *a = option_find_str(options, "mask", 0);
+ int *mask = parse_yolo_mask(a, &num);
+ int max_boxes = option_find_int_quiet(options, "max", 30);
+ layer l = make_yolo_layer(params.batch, params.w, params.h, num, total, mask, classes, max_boxes);
+ assert(l.outputs == params.inputs);
+
+ //l.max_boxes = option_find_int_quiet(options, "max", 90);
+ l.jitter = option_find_float(options, "jitter", .2);
+ l.focal_loss = option_find_int_quiet(options, "focal_loss", 0);
+
+ l.ignore_thresh = option_find_float(options, "ignore_thresh", .5);
+ l.truth_thresh = option_find_float(options, "truth_thresh", 1);
+ l.random = option_find_int_quiet(options, "random", 0);
+
+ char *map_file = option_find_str(options, "map", 0);
+ if (map_file) l.map = read_map(map_file);
+
+ a = option_find_str(options, "anchors", 0);
+ if (a) {
+ int len = strlen(a);
+ int n = 1;
+ int i;
+ for (i = 0; i < len; ++i) {
+ if (a[i] == ',') ++n;
+ }
+ for (i = 0; i < n && i < total*2; ++i) {
+ float bias = atof(a);
+ l.biases[i] = bias;
+ a = strchr(a, ',') + 1;
+ }
+ }
+ return l;
+}
+
layer parse_region(list *options, size_params params)
{
int coords = option_find_int(options, "coords", 4);
int classes = option_find_int(options, "classes", 20);
int num = option_find_int(options, "num", 1);
+ int max_boxes = option_find_int_quiet(options, "max", 30);
- params.w = option_find_int(options, "side", params.w);
- params.h = option_find_int(options, "side", params.h);
-
- layer l = make_region_layer(params.batch, params.w, params.h, num, classes, coords);
+ layer l = make_region_layer(params.batch, params.w, params.h, num, classes, coords, max_boxes);
assert(l.outputs == params.inputs);
l.log = option_find_int_quiet(options, "log", 0);
l.sqrt = option_find_int_quiet(options, "sqrt", 0);
l.softmax = option_find_int(options, "softmax", 0);
- l.max_boxes = option_find_int_quiet(options, "max",30);
+ l.focal_loss = option_find_int_quiet(options, "focal_loss", 0);
+ //l.max_boxes = option_find_int_quiet(options, "max",30);
l.jitter = option_find_float(options, "jitter", .2);
l.rescore = option_find_int_quiet(options, "rescore",0);
@@ -260,6 +327,7 @@
l.coord_scale = option_find_float(options, "coord_scale", 1);
l.object_scale = option_find_float(options, "object_scale", 1);
l.noobject_scale = option_find_float(options, "noobject_scale", 1);
+ l.mask_scale = option_find_float(options, "mask_scale", 1);
l.class_scale = option_find_float(options, "class_scale", 1);
l.bias_match = option_find_int_quiet(options, "bias_match",0);
@@ -276,7 +344,7 @@
for(i = 0; i < len; ++i){
if (a[i] == ',') ++n;
}
- for(i = 0; i < n; ++i){
+ for(i = 0; i < n && i < num*2; ++i){
float bias = atof(a);
l.biases[i] = bias;
a = strchr(a, ',')+1;
@@ -358,6 +426,23 @@
return layer;
}
+layer parse_reorg_old(list *options, size_params params)
+{
+ printf("\n reorg_old \n");
+ int stride = option_find_int(options, "stride", 1);
+ int reverse = option_find_int_quiet(options, "reverse", 0);
+
+ int batch, h, w, c;
+ h = params.h;
+ w = params.w;
+ c = params.c;
+ batch = params.batch;
+ if (!(h && w && c)) error("Layer before reorg layer must output image.");
+
+ layer layer = make_reorg_old_layer(batch, w, h, c, stride, reverse);
+ return layer;
+}
+
maxpool_layer parse_maxpool(list *options, size_params params)
{
int stride = option_find_int(options, "stride",1);
@@ -449,6 +534,15 @@
return l;
}
+layer parse_upsample(list *options, size_params params, network net)
+{
+
+ int stride = option_find_int(options, "stride", 2);
+ layer l = make_upsample_layer(params.batch, params.w, params.h, params.c, stride);
+ l.scale = option_find_float_quiet(options, "scale", 1);
+ return l;
+}
+
route_layer parse_route(list *options, size_params params, network net)
{
char *l = option_find(options, "layers");
@@ -528,18 +622,24 @@
net->inputs = option_find_int_quiet(options, "inputs", net->h * net->w * net->c);
net->max_crop = option_find_int_quiet(options, "max_crop",net->w*2);
net->min_crop = option_find_int_quiet(options, "min_crop",net->w);
+ net->flip = option_find_int_quiet(options, "flip", 1);
+ net->small_object = option_find_int_quiet(options, "small_object", 0);
net->angle = option_find_float_quiet(options, "angle", 0);
net->aspect = option_find_float_quiet(options, "aspect", 1);
net->saturation = option_find_float_quiet(options, "saturation", 1);
net->exposure = option_find_float_quiet(options, "exposure", 1);
net->hue = option_find_float_quiet(options, "hue", 0);
+ net->power = option_find_float_quiet(options, "power", 4);
if(!net->inputs && !(net->h && net->w && net->c)) error("No input parameters supplied");
char *policy_s = option_find_str(options, "policy", "constant");
net->policy = get_policy(policy_s);
net->burn_in = option_find_int_quiet(options, "burn_in", 0);
+#ifdef CUDNN_HALF
+ net->burn_in = 0;
+#endif
if(net->policy == STEP){
net->step = option_find_int(options, "step", 1);
net->scale = option_find_float(options, "scale", 1);
@@ -573,7 +673,7 @@
net->gamma = option_find_float(options, "gamma", 1);
net->step = option_find_int(options, "step", 1);
} else if (net->policy == POLY || net->policy == RANDOM){
- net->power = option_find_float(options, "power", 1);
+ //net->power = option_find_float(options, "power", 1);
}
net->max_batches = option_find_int(options, "max_batches", 0);
}
@@ -586,6 +686,11 @@
network parse_network_cfg(char *filename)
{
+ return parse_network_cfg_custom(filename, 0);
+}
+
+network parse_network_cfg_custom(char *filename, int batch)
+{
list *sections = read_cfg(filename);
node *n = sections->front;
if(!n) error("Config file has no sections");
@@ -602,10 +707,12 @@
params.w = net.w;
params.c = net.c;
params.inputs = net.inputs;
+ if (batch > 0) net.batch = batch;
params.batch = net.batch;
params.time_steps = net.time_steps;
params.net = net;
+ float bflops = 0;
size_t workspace_size = 0;
n = n->next;
int count = 0;
@@ -613,7 +720,7 @@
fprintf(stderr, "layer filters size input output\n");
while(n){
params.index = count;
- fprintf(stderr, "%5d ", count);
+ fprintf(stderr, "%4d ", count);
s = (section *)n->val;
options = s->options;
layer l = {0};
@@ -638,6 +745,8 @@
l = parse_cost(options, params);
}else if(lt == REGION){
l = parse_region(options, params);
+ }else if (lt == YOLO) {
+ l = parse_yolo(options, params);
}else if(lt == DETECTION){
l = parse_detection(options, params);
}else if(lt == SOFTMAX){
@@ -650,11 +759,15 @@
}else if(lt == MAXPOOL){
l = parse_maxpool(options, params);
}else if(lt == REORG){
- l = parse_reorg(options, params);
+ l = parse_reorg(options, params); }
+ else if (lt == REORG_OLD) {
+ l = parse_reorg_old(options, params);
}else if(lt == AVGPOOL){
l = parse_avgpool(options, params);
}else if(lt == ROUTE){
l = parse_route(options, params, net);
+ }else if (lt == UPSAMPLE) {
+ l = parse_upsample(options, params, net);
}else if(lt == SHORTCUT){
l = parse_shortcut(options, params, net);
}else if(lt == DROPOUT){
@@ -668,6 +781,8 @@
}else{
fprintf(stderr, "Type not recognized: %s\n", s->type);
}
+ l.onlyforward = option_find_int_quiet(options, "onlyforward", 0);
+ l.stopbackward = option_find_int_quiet(options, "stopbackward", 0);
l.dontload = option_find_int_quiet(options, "dontload", 0);
l.dontloadscales = option_find_int_quiet(options, "dontloadscales", 0);
option_unused(options);
@@ -682,10 +797,12 @@
params.c = l.out_c;
params.inputs = l.outputs;
}
+ if (l.bflops > 0) bflops += l.bflops;
}
free_list(sections);
net.outputs = get_network_output_size(net);
net.output = get_network_output(net);
+ printf("Total BFLOPS %5.3f \n", bflops);
if(workspace_size){
//printf("%ld\n", workspace_size);
#ifdef GPU
@@ -701,6 +818,8 @@
return net;
}
+
+
list *read_cfg(char *filename)
{
FILE *file = fopen(filename, "r");
@@ -829,7 +948,7 @@
}
#endif
fprintf(stderr, "Saving weights to %s\n", filename);
- FILE *fp = fopen(filename, "w");
+ FILE *fp = fopen(filename, "wb");
if(!fp) file_error(filename);
int major = 0;
@@ -969,23 +1088,28 @@
//return;
}
int num = l.n*l.c*l.size*l.size;
- if(0){
- fread(l.biases + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
- if (l.batch_normalize && (!l.dontloadscales)){
- fread(l.scales + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
- fread(l.rolling_mean + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
- fread(l.rolling_variance + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
+ fread(l.biases, sizeof(float), l.n, fp);
+ if (l.batch_normalize && (!l.dontloadscales)){
+ fread(l.scales, sizeof(float), l.n, fp);
+ fread(l.rolling_mean, sizeof(float), l.n, fp);
+ fread(l.rolling_variance, sizeof(float), l.n, fp);
+ if(0){
+ int i;
+ for(i = 0; i < l.n; ++i){
+ printf("%g, ", l.rolling_mean[i]);
+ }
+ printf("\n");
+ for(i = 0; i < l.n; ++i){
+ printf("%g, ", l.rolling_variance[i]);
+ }
+ printf("\n");
}
- fread(l.weights + ((l.n != 1374)?0:5*l.c*l.size*l.size), sizeof(float), num, fp);
- }else{
- fread(l.biases, sizeof(float), l.n, fp);
- if (l.batch_normalize && (!l.dontloadscales)){
- fread(l.scales, sizeof(float), l.n, fp);
- fread(l.rolling_mean, sizeof(float), l.n, fp);
- fread(l.rolling_variance, sizeof(float), l.n, fp);
+ if(0){
+ fill_cpu(l.n, 0, l.rolling_mean, 1);
+ fill_cpu(l.n, 0, l.rolling_variance, 1);
}
- fread(l.weights, sizeof(float), num, fp);
}
+ fread(l.weights, sizeof(float), num, fp);
if(l.adam){
fread(l.m, sizeof(float), num, fp);
fread(l.v, sizeof(float), num, fp);
@@ -1021,7 +1145,16 @@
fread(&major, sizeof(int), 1, fp);
fread(&minor, sizeof(int), 1, fp);
fread(&revision, sizeof(int), 1, fp);
- fread(net->seen, sizeof(int), 1, fp);
+ if ((major * 10 + minor) >= 2) {
+ printf("\n seen 64 \n");
+ uint64_t iseen = 0;
+ fread(&iseen, sizeof(uint64_t), 1, fp);
+ *net->seen = iseen;
+ }
+ else {
+ printf("\n seen 32 \n");
+ fread(net->seen, sizeof(int), 1, fp);
+ }
int transpose = (major > 1000) || (minor > 1000);
int i;
--
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