#define NULL ((void *)0)
typedef unsigned long size_t; // Customize by platform.
typedef long intptr_t;
typedef unsigned long uintptr_t;
typedef long scalar_t__; // Either arithmetic or pointer type.
/* By default, we understand bool (as a convenience). */
typedef int bool;
#define false 0
#define true 1

/* Forward declarations */

/* Type definitions */

/* Variables and functions */
int /*<<< orphan*/ exit(int);
int /*<<< orphan*/ printf(char *);
void exit_with_help(void) {
  printf("\n  \033[1mUSAGE\033[0m\n\n    bbfcreate [OPTION...]\n\n"
         "  \033[1mREQUIRED OPTIONS\033[0m\n\n"
         "    --positive-list : text file contains a list of positive files "
         "(cropped and scaled to the same size)\n"
         "    --background-list : text file contains a list of image files "
         "that don't contain any target objects\n"
         "    --negative-count : the number of negative examples we should "
         "collect from background files to initialize SVM\n"
         "    --working-dir : the directory to save progress and produce "
         "result model\n"
         "    --width : the width of positive image\n"
         "    --height : the height of positive image\n\n"
         "  \033[1mOTHER OPTIONS\033[0m\n\n"
         "    --base-dir : change the base directory so that the program can "
         "read images from there\n"
         "    --layer : how many layers needed for cascade classifier [DEFAULT "
         "TO 24]\n"
         "    --positive-criteria : what's the percentage of positive examples "
         "need to pass for the next layer [DEFAULT TO 0.9975]\n"
         "    --negative-criteria : what's the percentage of negative examples "
         "need to reject for the next layer [DEFAULT TO 0.5]\n"
         "    --balance : the balance weight for positive examples v.s. "
         "negative examples [DEFAULT TO 1.0]\n"
         "    --feature-number : how big our feature pool should be [DEFAULT "
         "TO 100 (thus, 100 * 100 = 10000 features)]\n\n");
  exit(-1);
}


x86 assembly (clang, -O0):
<exit_with_help>:
push   %rbp
mov    %rsp,%rbp
lea    0xed5(%rip),%rdi
call   1030 <printf@plt>
mov    $0xffffffff,%edi
call   1040 <exit@plt>

x86 assembly (clang, -O2):
<exit_with_help>:
push   %rax
lea    0xed8(%rip),%rdi
call   1030 <puts@plt>
mov    $0xffffffff,%edi
call   1040 <exit@plt>

LLVM IR (-O0):
@.str = [1197 x i8] c"\0A \1B[1mUSAGE\1B[0m\0A\0A bbfcreate [OPTION...]\0A\0A \1B[1mREQUIRED OPTIONS\1B[0m\0A\0A --positive-list : text file contains a list of positive files (cropped and scaled to the same size)\0A --background-list : text file contains a list of image files that don't contain any target objects\0A --negative-count : the number of negative examples we should collect from background files to initialize SVM\0A --working-dir : the directory to save progress and produce result model\0A --width : the width of positive image\0A --height : the height of positive image\0A\0A \1B[1mOTHER OPTIONS\1B[0m\0A\0A --base-dir : change the base directory so that the program can read images from there\0A --layer : how many layers needed for cascade classifier [DEFAULT TO 24]\0A --positive-criteria : what's the percentage of positive examples need to pass for the next layer [DEFAULT TO 0.9975]\0A --negative-criteria : what's the percentage of negative examples need to reject for the next layer [DEFAULT TO 0.5]\0A --balance : the balance weight for positive examples v.s. negative examples [DEFAULT TO 1.0]\0A --feature-number : how big our feature pool should be [DEFAULT TO 100 (thus, 100 * 100 = 10000 features)]\0A\0A\00"
define void @exit_with_help() {
%1 = call i32 @printf(i8* getelementptr inbounds ([1197 x i8], [1197 x i8]* @.str, i64 0, i64 0))
%2 = call i32 @exit(i32 -1)
unreachable
}

LLVM IR (-O2):
@str = [1196 x i8] c"\0A \1B[1mUSAGE\1B[0m\0A\0A bbfcreate [OPTION...]\0A\0A \1B[1mREQUIRED OPTIONS\1B[0m\0A\0A --positive-list : text file contains a list of positive files (cropped and scaled to the same size)\0A --background-list : text file contains a list of image files that don't contain any target objects\0A --negative-count : the number of negative examples we should collect from background files to initialize SVM\0A --working-dir : the directory to save progress and produce result model\0A --width : the width of positive image\0A --height : the height of positive image\0A\0A \1B[1mOTHER OPTIONS\1B[0m\0A\0A --base-dir : change the base directory so that the program can read images from there\0A --layer : how many layers needed for cascade classifier [DEFAULT TO 24]\0A --positive-criteria : what's the percentage of positive examples need to pass for the next layer [DEFAULT TO 0.9975]\0A --negative-criteria : what's the percentage of negative examples need to reject for the next layer [DEFAULT TO 0.5]\0A --balance : the balance weight for positive examples v.s. negative examples [DEFAULT TO 1.0]\0A --feature-number : how big our feature pool should be [DEFAULT TO 100 (thus, 100 * 100 = 10000 features)]\0A\00"
define void @exit_with_help() {
%1 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([1196 x i8], [1196 x i8]* @str, i64 0, i64 0))
%2 = tail call i32 @exit(i32 -1)
unreachable
}