Overview of the U19 Bundesliga 1st Group Stage Group G
The U19 Bundesliga represents a pinnacle for young football talent in Germany, showcasing the future stars of the sport. As we approach the 1st Group Stage Group G matches set for tomorrow, excitement builds around the potential outcomes and emerging talents. This group is particularly intriguing due to its mix of established youth academies and rising teams aiming to make their mark.
Teams in Group G
- Borussia Dortmund U19: Known for their robust youth system, Borussia Dortmund's team is always a strong contender. Their focus on developing technically gifted players makes them a formidable opponent.
- Bayern Munich U19: With a history of producing top-tier talent, Bayern Munich's youth squad is expected to perform well. Their strategic play and disciplined approach are key strengths.
- RB Leipzig U19: RB Leipzig has been rapidly rising in prominence, with a focus on innovative training methods and scouting. Their youthful energy and tactical flexibility are noteworthy.
- Hamburger SV U19: Hamburger SV has a rich history in youth development. Their team is known for resilience and adaptability, often surprising opponents with their tenacity.
Key Matchups and Predictions
Tomorrow's fixtures promise thrilling encounters as teams vie for supremacy in Group G. Here are some key matchups and expert betting predictions:
Borussia Dortmund U19 vs Bayern Munich U19
This clash between two giants of German football is highly anticipated. Dortmund's attacking flair will be tested against Bayern's defensive solidity. Betting experts suggest a narrow victory for Bayern, with odds favoring them due to their disciplined defense.
RB Leipzig U19 vs Hamburger SV U19
Leipzig's innovative tactics will face off against Hamburg's resilience. This match is expected to be closely contested, with Leipzig slightly favored due to their dynamic midfield play. Bettors might consider backing Leipzig to win with a small handicap.
Strategic Insights
Understanding the strategies employed by each team can provide deeper insights into potential outcomes:
- Borussia Dortmund U19: Focus on high pressing and quick transitions. Key players to watch include their forward line, known for their speed and finishing ability.
- Bayern Munich U19: Emphasis on maintaining possession and structured build-up play. Their midfielders are crucial in controlling the tempo of the game.
- RB Leipzig U19: Utilizes a fluid attacking system with interchangeable positions. Their creativity in the final third can be decisive.
- Hamburger SV U19: Relies on physicality and counter-attacks. Their ability to exploit spaces left by opponents can lead to unexpected goals.
Expert Betting Tips
For those interested in placing bets, here are some expert tips based on current form and analysis:
- Consider backing underdogs like Hamburger SV when they play away, as they have shown capability to secure points against stronger teams.
- Look for value in betting on over/under goals in matches involving Borussia Dortmund due to their attacking prowess.
- Monitor player form closely; individual performances can significantly impact match outcomes.
Tactical Formations and Key Players
Each team's formation and key players play a crucial role in determining match dynamics:
- Borussia Dortmund U19: Likely to employ a 4-2-3-1 formation, focusing on wing play. Key player: A dynamic winger known for his dribbling skills.
- Bayern Munich U19: Expected to use a 4-3-3 setup, emphasizing width and crosses into the box. Key player: A central midfielder with excellent vision.
- RB Leipzig U19: Might opt for a fluid 4-2-3-1/4-3-3 hybrid, allowing creative freedom. Key player: An attacking midfielder with prolific goal-scoring ability.
- Hamburger SV U19: Could stick with a traditional 4-4-2, focusing on defensive solidity and quick breaks. Key player: A tenacious central defender known for leadership.
Past Performances and Trends
Analyzing past performances can offer valuable insights into potential outcomes:
- Borussia Dortmund U19: Consistently strong in home matches, often dominating possession and scoring early goals.
- Bayern Munich U19: Known for late-game comebacks, their ability to maintain composure under pressure is notable.
- RB Leipzig U19: Exhibits an upward trend with increased confidence in away fixtures, often securing vital points.
- Hamburger SV U19: Demonstrates resilience in tight matches, often earning draws through disciplined defending.
Statistical Analysis
A deeper dive into statistics provides further clarity on team strengths and weaknesses:
- Borussia Dortmund U19: High average possession percentage, indicating control over games. Strongest in aerial duels.
- Bayern Munich U19: Lowest goals conceded per game among group teams, showcasing defensive strength. High pass completion rate.
- RB Leipzig U19: Leading in assists per game, reflecting their creative midfield setup. Quick counter-attacks are a trademark.
- Hamburger SV U19: Highest tackle success rate, emphasizing their defensive strategy. Effective in set-piece situations.
Match Previews and Tactical Breakdowns
Borussia Dortmund U19 vs Bayern Munich U19 - Tactical Breakdown
Dortmund will likely aim to exploit Bayern's high defensive line with quick forwards making runs behind the defense. Bayern, on the other hand, will focus on controlling the midfield battle and exploiting set-piece opportunities.
RB Leipzig U19 vs Hamburger SV U19 - Tactical Breakdown
Leipzig's strategy will revolve around maintaining possession and utilizing their wingers to stretch Hamburg's defense. Hamburg will look to absorb pressure and launch counter-attacks through pacey forwards.
Potential Impact of Weather Conditions
<|file_sep|>#include "lib.h"
void loop(void) {
int8_t i;
for (i = 'A'; i <= 'Z'; i++) {
putc(i);
}
putc('n');
}
<|repo_name|>lukasg/avr-gcc-musical-keyboard<|file_sep|>/lib.c
#include "lib.h"
static int8_t pin_bitmask[PIN_COUNT] = {
0x01,
0x02,
0x04,
0x08,
0x10,
0x20,
0x40,
0x80
};
static int8_t pin_state[PIN_COUNT];
void init(void) {
DDRA = PINB = DDRC = DDRD = DDRF = DDRJ = DDRK = DDRL = DDRM =
DDRN = PORTA = PORTB = PORTC = PORTD = PORTE = PORTF =
PORTJ = PORTK = PORTL = PORTM = PORTN =
0xFF;
}
int8_t get_pin(int8_t pin) {
if (pin > PIN_COUNT)
return -1;
return (PINB & pin_bitmask[pin]) ? HIGH : LOW;
}
int8_t set_pin(int8_t pin) {
if (pin > PIN_COUNT)
return -1;
PINB |= pin_bitmask[pin];
return HIGH;
}
int8_t clear_pin(int8_t pin) {
if (pin > PIN_COUNT)
return -1;
PINB &= ~pin_bitmask[pin];
return LOW;
}
int8_t toggle_pin(int8_t pin) {
if (pin > PIN_COUNT)
return -1;
PINB ^= pin_bitmask[pin];
return get_pin(pin);
}
void putc(int8_t c) {
while ((UCSR0A & _BV(UDRE0)) == false);
UDR0 = c;
}
int8_t getch(void) {
while ((UCSR0A & _BV(RXC0)) == false);
return UDR0;
}
<|repo_name|>lukasg/avr-gcc-musical-keyboard<|file_sep|>/main.c
#include "lib.h"
int main(void) {
init();
loop();
}
<|file_sep|>#include "lib.h"
#include "midi.h"
#define NOTES_PER_OCTAVE (12)
#define NOTE_C (12)
#define NOTE_CS (13)
#define NOTE_D (14)
#define NOTE_DS (15)
#define NOTE_E (16)
#define NOTE_F (17)
#define NOTE_FS (18)
#define NOTE_G (19)
#define NOTE_GS (20)
#define NOTE_A (21)
#define NOTE_AS (22)
#define NOTE_B (23)
static uint16_t note[NOTES_PER_OCTAVE] =
{
NOTE_C,
NOTE_CS,
NOTE_D,
NOTE_DS,
NOTE_E,
NOTE_F,
NOTE_FS,
NOTE_G,
NOTE_GS,
NOTE_A,
NOTE_AS,
NOTE_B
};
static uint16_t octave[9] =
{
note[NOTE_C] * pow(2,0),
note[NOTE_C] * pow(2,1),
note[NOTE_C] * pow(2,2),
note[NOTE_C] * pow(2,3),
note[NOTE_C] * pow(2,4),
note[NOTE_C] * pow(2,5),
note[NOTE_C] * pow(2,6),
note[NOTE_C] * pow(2,7),
note[NOTE_C] * pow(2,8)
};
static uint16_t midi_note_to_frequency(uint16_t note);
void loop(void) {
uint16_t midi_note;
uint16_t frequency;
while (true) {
midi_note = getch();
if ((midi_note >= NOTE_C) && (midi_note <= NOTE_B)) {
midi_note += getch() * NOTES_PER_OCTAVE;
}
frequency = midi_note_to_frequency(midi_note);
if (frequency > F_CPU / MIDI_MAX_PULSE_WIDTH / MIDI_MAX_NOTE_DIVISOR + MIDI_MIN_NOTE_DIVISOR / MIDI_MAX_PULSE_WIDTH) {
midi_note_to_frequency(midi_note + NOTES_PER_OCTAVE);
} else if (frequency <= F_CPU / MIDI_MAX_PULSE_WIDTH / MIDI_MIN_NOTE_DIVISOR + MIDI_MAX_NOTE_DIVISOR / MIDI_MAX_PULSE_WIDTH) {
midi_note_to_frequency(midi_note - NOTES_PER_OCTAVE);
}
frequency *= MIDI_NOTE_DIVISOR;
set_pin(PIN_7);
delay(frequency);
clear_pin(PIN_7);
delay(MIDI_MAX_PULSE_WIDTH - frequency);
}
}
uint16_t midi_note_to_frequency(uint16_t note) {
int octave_index;
int note_index;
octave_index = note / NOTES_PER_OCTAVE;
note_index = note % NOTES_PER_OCTAVE;
return octave[octave_index] + note[note_index];
}
<|repo_name|>lukasg/avr-gcc-musical-keyboard<|file_sep|>/Makefile
CC=avr-gcc
OBJCOPY=avr-objcopy
CFLAGS=-Os -Wall -mmcu=atmega328p
LDFLAGS=-Wl,-Map=output.map
SRC=$(wildcard *.c)
all: output.hex
output.hex: output.o
mkdir -p build/
rm -f build/*
mv output.o build/
cd build && $(OBJCOPY) -j .text -j .data -O ihex output.o ../output.hex
output.o: $(SRC)
mkdir -p build/
rm -f build/*
mv $(SRC) build/
cd build && $(CC) $(CFLAGS) $(LDFLAGS) *.c
clean:
rm -rf build/
rm output.hex
<|file_sep|>#ifndef LIB_H
#define LIB_H
#include "config.h"
#include "util/delay.h"
#include "util/atomic.h"
#include "util/twi.h"
#include "util/delay_basic.h"
#include "util/crc16.h"
#include "util/crc8.h"
#include "iobitmaps.h"
#include "iom328p.h"
typedef uint8_t int8_t;
typedef uint8_t bool;
enum bool_values { false=0,true };
void init(void);
int8_t get_pin(int8_t pin);
int8_t set_pin(int8_t pin);
int8_t clear_pin(int8_t pin);
int8_t toggle_pin(int8_t pin);
void putc(int8_t c);
int8_t getch(void);
#endif // LIB_H
<|file_sep|>#ifndef MIDI_H
#define MIDI_H
#ifndef F_CPU
# define F_CPU (16000000UL)
#endif
#ifndef MIDI_MAX_PULSE_WIDTH
# define MIDI_MAX_PULSE_WIDTH (10)
#endif
#ifndef MIDI_MIN_NOTE_DIVISOR
# define MIDI_MIN_NOTE_DIVISOR (5)
#endif
#ifndef MIDI_MAX_NOTE_DIVISOR
# define MIDI_MAX_NOTE_DIVISOR (15)
#endif
#endif //MIDI_H
<|repo_name|>zhaoyangyong/CVPR2021_Towards_Universal_Saliency_Detection_via_Simultaneous_Foreground_and_Background_Supervision<|file_sep|>/models/SANet.py
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import models
from .BasicLayers import BasicConv
from .BasicLayers import BasicRFB
from .BasicLayers import PyramidPoolingModule
class SANet(nn.Module):
def __init__(self):
super(SANet,self).__init__()
resnet50_model=models.resnet50(pretrained=True)
self.conv1=resnet50_model.conv1
# self.bn1=resnet50_model.bn1
# self.relu=resnet50_model.relu
# self.maxpool=resnet50_model.maxpool
# self.layer1=resnet50_model.layer1
# self.layer2=resnet50_model.layer2
# self.layer3=resnet50_model.layer3
# self.layer4=resnet50_model.layer4
# for n,p in self.layer4.named_parameters():
# if 'conv' not in n:
# p.requires_grad=False
# self.BAS_layer1=self._make_layer(Bottleneck,[256]*2+ [512],1)
# self.BAS_layer2=self._make_layer(Bottleneck,[512]*6+ [1024],1)
# self.BAS_layer3=self._make_layer(Bottleneck,[1024]*6+ [2048],1)
# self.RFB_1=BasicRFB(in_channels=1024,out_channels=512,kernel_size=5,stride=1,padding=2,dilation=2)
# self.RFB_2=BasicRFB(in_channels=2048,out_channels=1024,kernel_size=5,stride=1,padding=2,dilation=2)
def forward(self,x):
x=self.conv1(x)
x=F.relu(x)
x=self.maxpool(x)
x=self.layer1(x)
x=self.layer2(x)
x=self.layer3(x)
feature_map=x #shape:(b,c,h,w)=(b,1024,h,w)
x=self.layer4(x)
feature_map=torch.cat((feature_map,x),dim=1)
feature_map=F.interpolate(feature_map,scale_factor=2)
feature_map=self.PPM(feature_map)
feature_map=F.interpolate(feature_map,scale_factor=32,size=(224,224),mode='bilinear',align_corners=True)
return feature_map
def _make_layer(self,BasicBlock,inplanes=[],blocks,norm_layer=None):
stride=[None]*(blocks+1)
stride[-1]=2
stride=tuple(stride)
layers=[]
layers.append(BasicBlock(inplanes[0],inplanes[-1],stride,padding=[None]*len(inplanes)+[6],dilation=[None]*len(inplanes)+[6],norm_layer=norm_layer))
for i in range(1,len(inplanes)):
stride=[None]*blocks+[i]
stride=tuple(stride)
layers.append(BasicBlock(inplanes[i],inplanes[i],stride,padding=[None]*blocks+[6],dilation=[None]*blocks+[6],norm_layer=norm_layer))
layers=tuple(layers)
return nn.Sequential(*layers)
if __name__=='__main__':
a=torch.rand([5,64]+[56]*2).cuda()
model=SANet().cuda()
output=model(a)
print(output.shape)<|repo_name|>zhaoyangyong/CVPR2021_Towards