YOLO v3

.gitattributes

@@ -53,3 +53,5 @@ Qwen2-VL/Qwen2-VL-2B-Instruct-GGUF/Qwen2-VL-2B-Instruct-Q4_K_M.gguf filter=lfs d
 Qwen2-VL/Qwen2-VL-2B-Instruct-GGUF/Qwen2-VL-2B-Instruct-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
 Qwen2-VL/Qwen2-VL-2B-Instruct-GGUF/Qwen2-VL-2B-Instruct-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
 YOLO/yolov2-tiny/yolov2-tiny-voc.weights filter=lfs diff=lfs merge=lfs -text
+YOLO/yolo-v3/openimages/yolov3-openimages.weights filter=lfs diff=lfs merge=lfs -text
+YOLO/yolo-v3/v3/yolov3.weights filter=lfs diff=lfs merge=lfs -text

YOLO/yolo-v3/modelSelect.txt

@@ -0,0 +1,3 @@
+v3/yolov3.cfg
+v3/yolov3.weights
+v3/coco.names

YOLO/yolo-v3/openimages/openimages.names

@@ -0,0 +1,601 @@
+Tortoise
+Container
+Magpie
+Sea turtle
+Football
+Ambulance
+Ladder
+Toothbrush
+Syringe
+Sink
+Toy
+Organ
+Cassette deck
+Apple
+Human eye
+Cosmetics
+Paddle
+Snowman
+Beer
+Chopsticks
+Human beard
+Bird
+Parking meter
+Traffic light
+Croissant
+Cucumber
+Radish
+Towel
+Doll
+Skull
+Washing machine
+Glove
+Tick
+Belt
+Sunglasses
+Banjo
+Cart
+Ball
+Backpack
+Bicycle
+Home appliance
+Centipede
+Boat
+Surfboard
+Boot
+Headphones
+Hot dog
+Shorts
+Fast food
+Bus
+Boy
+Screwdriver
+Bicycle wheel
+Barge
+Laptop
+Miniskirt
+Drill
+Dress
+Bear
+Waffle
+Pancake
+Brown bear
+Woodpecker
+Blue jay
+Pretzel
+Bagel
+Tower
+Teapot
+Person
+Bow and arrow
+Swimwear
+Beehive
+Brassiere
+Bee
+Bat
+Starfish
+Popcorn
+Burrito
+Chainsaw
+Balloon
+Wrench
+Tent
+Vehicle registration plate
+Lantern
+Toaster
+Flashlight
+Billboard
+Tiara
+Limousine
+Necklace
+Carnivore
+Scissors
+Stairs
+Computer keyboard
+Printer
+Traffic sign
+Chair
+Shirt
+Poster
+Cheese
+Sock
+Fire hydrant
+Land vehicle
+Earrings
+Tie
+Watercraft
+Cabinetry
+Suitcase
+Muffin
+Bidet
+Snack
+Snowmobile
+Clock
+Medical equipment
+Cattle
+Cello
+Jet ski
+Camel
+Coat
+Suit
+Desk
+Cat
+Bronze sculpture
+Juice
+Gondola
+Beetle
+Cannon
+Computer mouse
+Cookie
+Office building
+Fountain
+Coin
+Calculator
+Cocktail
+Computer monitor
+Box
+Stapler
+Christmas tree
+Cowboy hat
+Hiking equipment
+Studio couch
+Drum
+Dessert
+Wine rack
+Drink
+Zucchini
+Ladle
+Human mouth
+Dairy
+Dice
+Oven
+Dinosaur
+Ratchet
+Couch
+Cricket ball
+Winter melon
+Spatula
+Whiteboard
+Pencil sharpener
+Door
+Hat
+Shower
+Eraser
+Fedora
+Guacamole
+Dagger
+Scarf
+Dolphin
+Sombrero
+Tin can
+Mug
+Tap
+Harbor seal
+Stretcher
+Can opener
+Goggles
+Human body
+Roller skates
+Coffee cup
+Cutting board
+Blender
+Plumbing fixture
+Stop sign
+Office supplies
+Volleyball
+Vase
+Slow cooker
+Wardrobe
+Coffee
+Whisk
+Paper towel
+Personal care
+Food
+Sun hat
+Tree house
+Flying disc
+Skirt
+Gas stove
+Salt and pepper shakers
+Mechanical fan
+Face powder
+Fax
+Fruit
+French fries
+Nightstand
+Barrel
+Kite
+Tart
+Treadmill
+Fox
+Flag
+Horn
+Window blind
+Human foot
+Golf cart
+Jacket
+Egg
+Street light
+Guitar
+Pillow
+Human leg
+Isopod
+Grape
+Human ear
+Power plugs and sockets
+Panda
+Giraffe
+Woman
+Door handle
+Rhinoceros
+Bathtub
+Goldfish
+Houseplant
+Goat
+Baseball bat
+Baseball glove
+Mixing bowl
+Marine invertebrates
+Kitchen utensil
+Light switch
+House
+Horse
+Stationary bicycle
+Hammer
+Ceiling fan
+Sofa bed
+Adhesive tape
+Harp
+Sandal
+Bicycle helmet
+Saucer
+Harpsichord
+Human hair
+Heater
+Harmonica
+Hamster
+Curtain
+Bed
+Kettle
+Fireplace
+Scale
+Drinking straw
+Insect
+Hair dryer
+Kitchenware
+Indoor rower
+Invertebrate
+Food processor
+Bookcase
+Refrigerator
+Wood-burning stove
+Punching bag
+Common fig
+Cocktail shaker
+Jaguar
+Golf ball
+Fashion accessory
+Alarm clock
+Filing cabinet
+Artichoke
+Table
+Tableware
+Kangaroo
+Koala
+Knife
+Bottle
+Bottle opener
+Lynx
+Lavender
+Lighthouse
+Dumbbell
+Human head
+Bowl
+Humidifier
+Porch
+Lizard
+Billiard table
+Mammal
+Mouse
+Motorcycle
+Musical instrument
+Swim cap
+Frying pan
+Snowplow
+Bathroom cabinet
+Missile
+Bust
+Man
+Waffle iron
+Milk
+Ring binder
+Plate
+Mobile phone
+Baked goods
+Mushroom
+Crutch
+Pitcher
+Mirror
+Lifejacket
+Table tennis racket
+Pencil case
+Musical keyboard
+Scoreboard
+Briefcase
+Kitchen knife
+Nail
+Tennis ball
+Plastic bag
+Oboe
+Chest of drawers
+Ostrich
+Piano
+Girl
+Plant
+Potato
+Hair spray
+Sports equipment
+Pasta
+Penguin
+Pumpkin
+Pear
+Infant bed
+Polar bear
+Mixer
+Cupboard
+Jacuzzi
+Pizza
+Digital clock
+Pig
+Reptile
+Rifle
+Lipstick
+Skateboard
+Raven
+High heels
+Red panda
+Rose
+Rabbit
+Sculpture
+Saxophone
+Shotgun
+Seafood
+Submarine sandwich
+Snowboard
+Sword
+Picture frame
+Sushi
+Loveseat
+Ski
+Squirrel
+Tripod
+Stethoscope
+Submarine
+Scorpion
+Segway
+Training bench
+Snake
+Coffee table
+Skyscraper
+Sheep
+Television
+Trombone
+Tea
+Tank
+Taco
+Telephone
+Torch
+Tiger
+Strawberry
+Trumpet
+Tree
+Tomato
+Train
+Tool
+Picnic basket
+Cooking spray
+Trousers
+Bowling equipment
+Football helmet
+Truck
+Measuring cup
+Coffeemaker
+Violin
+Vehicle
+Handbag
+Paper cutter
+Wine
+Weapon
+Wheel
+Worm
+Wok
+Whale
+Zebra
+Auto part
+Jug
+Pizza cutter
+Cream
+Monkey
+Lion
+Bread
+Platter
+Chicken
+Eagle
+Helicopter
+Owl
+Duck
+Turtle
+Hippopotamus
+Crocodile
+Toilet
+Toilet paper
+Squid
+Clothing
+Footwear
+Lemon
+Spider
+Deer
+Frog
+Banana
+Rocket
+Wine glass
+Countertop
+Tablet computer
+Waste container
+Swimming pool
+Dog
+Book
+Elephant
+Shark
+Candle
+Leopard
+Axe
+Hand dryer
+Soap dispenser
+Porcupine
+Flower
+Canary
+Cheetah
+Palm tree
+Hamburger
+Maple
+Building
+Fish
+Lobster
+Asparagus
+Furniture
+Hedgehog
+Airplane
+Spoon
+Otter
+Bull
+Oyster
+Horizontal bar
+Convenience store
+Bomb
+Bench
+Ice cream
+Caterpillar
+Butterfly
+Parachute
+Orange
+Antelope
+Beaker
+Moths and butterflies
+Window
+Closet
+Castle
+Jellyfish
+Goose
+Mule
+Swan
+Peach
+Coconut
+Seat belt
+Raccoon
+Chisel
+Fork
+Lamp
+Camera
+Squash
+Racket
+Human face
+Human arm
+Vegetable
+Diaper
+Unicycle
+Falcon
+Chime
+Snail
+Shellfish
+Cabbage
+Carrot
+Mango
+Jeans
+Flowerpot
+Pineapple
+Drawer
+Stool
+Envelope
+Cake
+Dragonfly
+Sunflower
+Microwave oven
+Honeycomb
+Marine mammal
+Sea lion
+Ladybug
+Shelf
+Watch
+Candy
+Salad
+Parrot
+Handgun
+Sparrow
+Van
+Grinder
+Spice rack
+Light bulb
+Corded phone
+Sports uniform
+Tennis racket
+Wall clock
+Serving tray
+Kitchen & dining room table
+Dog bed
+Cake stand
+Cat furniture
+Bathroom accessory
+Facial tissue holder
+Pressure cooker
+Kitchen appliance
+Tire
+Ruler
+Luggage and bags
+Microphone
+Broccoli
+Umbrella
+Pastry
+Grapefruit
+Band-aid
+Animal
+Bell pepper
+Turkey
+Lily
+Pomegranate
+Doughnut
+Glasses
+Human nose
+Pen
+Ant
+Car
+Aircraft
+Human hand
+Skunk
+Teddy bear
+Watermelon
+Cantaloupe
+Dishwasher
+Flute
+Balance beam
+Sandwich
+Shrimp
+Sewing machine
+Binoculars
+Rays and skates
+Ipod
+Accordion
+Willow
+Crab
+Crown
+Seahorse
+Perfume
+Alpaca
+Taxi
+Canoe
+Remote control
+Wheelchair
+Rugby ball
+Armadillo
+Maracas
+Helmet

YOLO/yolo-v3/openimages/yolov3-openimages.cfg

@@ -0,0 +1,789 @@
+[net]
+# Testing
+ batch=1
+ subdivisions=1
+# Training
+batch=64
+subdivisions=16
+width=608
+height=608
+channels=3
+momentum=0.9
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.001
+burn_in=5000
+max_batches = 500200
+policy=steps
+steps=400000,450000
+scales=.1,.1
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+######################
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=1818
+activation=linear
+
+
+[yolo]
+mask = 6,7,8
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=601
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = -1, 61
+
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=1818
+activation=linear
+
+
+[yolo]
+mask = 3,4,5
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=601
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
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+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=601
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+

YOLO/yolo-v3/openimages/yolov3-openimages.weights

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YOLO/yolo-v3/v3/coco.names

@@ -0,0 +1,80 @@
+person
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+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
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+clock
+vase
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+teddy bear
+hair drier
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YOLO/yolo-v3/v3/yolov3.cfg

@@ -0,0 +1,789 @@
+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=16
+width=416
+height=416
+channels=3
+momentum=0.9
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.001
+burn_in=1000
+max_batches = 500200
+policy=steps
+steps=400000,450000
+scales=.1,.1
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
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+size=1
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+activation=leaky
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+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
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+filters=64
+size=1
+stride=1
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+activation=leaky
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+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
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+[shortcut]
+from=-3
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+[convolutional]
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+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
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+
+[convolutional]
+batch_normalize=1
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+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
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+size=3
+stride=1
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+activation=leaky
+
+[shortcut]
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+[convolutional]
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+size=1
+stride=1
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+[convolutional]
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+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
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+[convolutional]
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+filters=512
+size=3
+stride=1
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+activation=leaky
+
+[shortcut]
+from=-3
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+
+[convolutional]
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+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
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+
+
+[convolutional]
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+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
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+pad=1
+activation=leaky
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+[shortcut]
+from=-3
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+
+
+[convolutional]
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+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
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+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
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+[shortcut]
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+activation=leaky
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+[convolutional]
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+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[shortcut]
+from=-3
+activation=linear
+
+######################
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
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+stride=1
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+filters=1024
+activation=leaky
+
+[convolutional]
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+size=1
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+activation=leaky
+
+[convolutional]
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+stride=1
+pad=1
+filters=1024
+activation=leaky
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+[convolutional]
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+stride=1
+pad=1
+activation=leaky
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+[convolutional]
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+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 6,7,8
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = -1, 61
+
+
+
+[convolutional]
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+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
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+stride=1
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+filters=512
+activation=leaky
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+[convolutional]
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+size=1
+stride=1
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+activation=leaky
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+[convolutional]
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+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 3,4,5
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = -1, 36
+
+
+
+[convolutional]
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+filters=128
+size=1
+stride=1
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+activation=leaky
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+[convolutional]
+size=1
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+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 0,1,2
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+

YOLO/yolo-v3/v3/yolov3.weights

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:523e4e69e1d015393a1b0a441cef1d9c7659e3eb2d7e15f793f060a21b32f297
+size 248007048