diff --git a/PyTorch-to-TensorFlow-Model-Conversion/FullyConvolutionalResnet18.py b/PyTorch-to-TensorFlow-Model-Conversion/FullyConvolutionalResnet18.py new file mode 100644 index 000000000..aac14f364 --- /dev/null +++ b/PyTorch-to-TensorFlow-Model-Conversion/FullyConvolutionalResnet18.py @@ -0,0 +1,140 @@ +import cv2 +import numpy as np +import tensorflow as tf +import torch +from albumentations import ( + Compose, + Normalize, +) +from pytorch2keras.converter import pytorch_to_keras +from torch.autograd import Variable + +from PyTorchFullyConvolutionalResnet18 import FullyConvolutionalResnet18 + + +def converted_fully_convolutional_resnet18( + input_tensor, pretrained_resnet=True, +): + # define input tensor + input_var = Variable(torch.FloatTensor(input_tensor)) + + # get PyTorch ResNet18 model + model_to_transfer = FullyConvolutionalResnet18(pretrained=pretrained_resnet) + model_to_transfer.eval() + + # convert PyTorch model to Keras + model = pytorch_to_keras( + model_to_transfer, + input_var, + [input_var.shape[-3:]], + change_ordering=True, + verbose=False, + name_policy="keep", + ) + + return model + + +if __name__ == "__main__": + # read ImageNet class ids to a list of labels + with open("imagenet_classes.txt") as f: + labels = [line.strip() for line in f.readlines()] + + # read image + original_image = cv2.imread("camel.jpg") + + # convert original image to RGB format + image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB) + + # transform input image: + transform = Compose( + [ + Normalize( + # subtract mean + mean=(0.485, 0.456, 0.406), + # divide by standard deviation + std=(0.229, 0.224, 0.225), + ), + ], + ) + # apply image transformations, (725, 1920, 3) + image = transform(image=image)["image"] + + # NHWC: (1, 725, 1920, 3) + predict_image = tf.expand_dims(image, 0) + # NCHW: (1, 3, 725, 1920) + image = np.transpose(tf.expand_dims(image, 0).numpy(), [0, 3, 1, 2]) + + # get transferred torch ResNet18 with pre-trained ImageNet weights + model = converted_fully_convolutional_resnet18( + input_tensor=image, pretrained_resnet=True, + ) + + # Perform inference. + # Instead of a 1×1000 vector, we will get a + # 1×1000×n×m output ( i.e. a probability map + # of size n × m for each 1000 class, + # where n and m depend on the size of the image). + preds = model.predict(predict_image) + # NHWC: (1, 3, 8, 1000) back to NCHW: (1, 1000, 3, 8) + preds = tf.transpose(preds, (0, 3, 1, 2)) + preds = tf.nn.softmax(preds, axis=1) + print("Response map shape : ", preds.shape) + + # find the class with the maximum score in the n x m output map + pred = tf.math.reduce_max(preds, axis=1) + class_idx = tf.math.argmax(preds, axis=1) + + row_max = tf.math.reduce_max(pred, axis=1) + row_idx = tf.math.argmax(pred, axis=1) + + col_idx = tf.math.argmax(row_max, axis=1) + + predicted_class = tf.gather_nd( + class_idx, (0, tf.gather_nd(row_idx, (0, col_idx[0])), col_idx[0]), + ) + + # print top predicted class + print("Predicted Class : ", labels[predicted_class], predicted_class) + + # find the n × m score map for the predicted class + score_map = tf.expand_dims(preds[0, predicted_class, :, :], 0).numpy() + score_map = score_map[0] + + # resize score map to the original image size + score_map = cv2.resize( + score_map, (original_image.shape[1], original_image.shape[0]), + ) + + # binarize score map + _, score_map_for_contours = cv2.threshold( + score_map, 0.25, 1, type=cv2.THRESH_BINARY, + ) + + score_map_for_contours = score_map_for_contours.astype(np.uint8).copy() + + # Find the contour of the binary blob + contours, _ = cv2.findContours( + score_map_for_contours, mode=cv2.RETR_EXTERNAL, method=cv2.CHAIN_APPROX_SIMPLE, + ) + + # find bounding box around the object. + rect = cv2.boundingRect(contours[0]) + + # apply score map as a mask to original image + score_map = score_map - np.min(score_map[:]) + score_map = score_map / np.max(score_map[:]) + + score_map = cv2.cvtColor(score_map, cv2.COLOR_GRAY2BGR) + masked_image = (original_image * score_map).astype(np.uint8) + + # display bounding box + cv2.rectangle( + masked_image, rect[:2], (rect[0] + rect[2], rect[1] + rect[3]), (0, 0, 255), 2, + ) + + # display images + cv2.imshow("Original Image", original_image) + cv2.imshow("scaled_score_map", score_map) + cv2.imshow("activations_and_bbox", masked_image) + cv2.waitKey(0) diff --git a/PyTorch-to-TensorFlow-Model-Conversion/PyTorchFullyConvolutionalResnet18.py b/PyTorch-to-TensorFlow-Model-Conversion/PyTorchFullyConvolutionalResnet18.py new file mode 100644 index 000000000..f9fc1c2f3 --- /dev/null +++ b/PyTorch-to-TensorFlow-Model-Conversion/PyTorchFullyConvolutionalResnet18.py @@ -0,0 +1,60 @@ +import torch +import torch.nn as nn +from torch.hub import load_state_dict_from_url +from torchvision import models + + +# Define the architecture by modifying resnet. +# Original code is here +# https://github.com/pytorch/vision/blob/b2e95657cd5f389e3973212ba7ddbdcc751a7878/torchvision/models/resnet.py +class FullyConvolutionalResnet18(models.ResNet): + def __init__(self, num_classes=1000, pretrained=False, **kwargs): + + # Start with standard resnet18 defined here + # https://github.com/pytorch/vision/blob/b2e95657cd5f389e3973212ba7ddbdcc751a7878/torchvision/models/resnet.py + super().__init__( + block=models.resnet.BasicBlock, + layers=[2, 2, 2, 2], + num_classes=num_classes, + **kwargs, + ) + if pretrained: + state_dict = load_state_dict_from_url( + models.resnet.model_urls["resnet18"], progress=True, + ) + self.load_state_dict(state_dict) + + # Replace AdaptiveAvgPool2d with standard AvgPool2d + # https://github.com/pytorch/vision/blob/b2e95657cd5f389e3973212ba7ddbdcc751a7878/torchvision/models/resnet.py#L153-L154 + self.avgpool = nn.AvgPool2d((7, 7)) + + # Add final Convolution Layer. + self.last_conv = torch.nn.Conv2d( + in_channels=self.fc.in_features, out_channels=num_classes, kernel_size=1, + ) + self.last_conv.weight.data.copy_( + self.fc.weight.data.view(*self.fc.weight.data.shape, 1, 1), + ) + self.last_conv.bias.data.copy_(self.fc.bias.data) + + # Reimplementing forward pass. + # Replacing the following code + # https://github.com/pytorch/vision/blob/b2e95657cd5f389e3973212ba7ddbdcc751a7878/torchvision/models/resnet.py#L197-L213 + def _forward_impl(self, x): + # Standard forward for resnet18 + x = self.conv1(x) + x = self.bn1(x) + x = self.relu(x) + x = self.maxpool(x) + + x = self.layer1(x) + x = self.layer2(x) + x = self.layer3(x) + x = self.layer4(x) + x = self.avgpool(x) + + # Notice, there is no forward pass + # through the original fully connected layer. + # Instead, we forward pass through the last conv layer + x = self.last_conv(x) + return x diff --git a/PyTorch-to-TensorFlow-Model-Conversion/README.md b/PyTorch-to-TensorFlow-Model-Conversion/README.md new file mode 100644 index 000000000..192924f97 --- /dev/null +++ b/PyTorch-to-TensorFlow-Model-Conversion/README.md @@ -0,0 +1,12 @@ +This contains the code for **PyTorch to Tensorflow Model Conversion**. For more information - visit +[**PyTorch to Tensorflow Model Conversion**](https://www.learnopencv.com/pytorch-to-tensorflow-model-conversion/) + +# AI Courses by OpenCV + +Want to become an expert in AI? [AI Courses by OpenCV](https://opencv.org/courses/) is a great place to start. + + +

+ +

+ diff --git a/PyTorch-to-TensorFlow-Model-Conversion/camel.jpg b/PyTorch-to-TensorFlow-Model-Conversion/camel.jpg new file mode 100644 index 000000000..f1eae1f94 Binary files /dev/null and b/PyTorch-to-TensorFlow-Model-Conversion/camel.jpg differ diff --git a/PyTorch-to-TensorFlow-Model-Conversion/imagenet_classes.txt b/PyTorch-to-TensorFlow-Model-Conversion/imagenet_classes.txt new file mode 100644 index 000000000..a509c0074 --- /dev/null +++ b/PyTorch-to-TensorFlow-Model-Conversion/imagenet_classes.txt @@ -0,0 +1,1000 @@ +tench, Tinca tinca +goldfish, Carassius auratus +great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias +tiger shark, Galeocerdo cuvieri +hammerhead, hammerhead shark +electric ray, crampfish, numbfish, torpedo +stingray +cock +hen +ostrich, Struthio camelus +brambling, Fringilla montifringilla +goldfinch, Carduelis carduelis +house finch, linnet, Carpodacus mexicanus +junco, snowbird +indigo bunting, indigo finch, indigo bird, Passerina cyanea +robin, American robin, Turdus migratorius +bulbul +jay +magpie +chickadee +water ouzel, dipper +kite +bald eagle, American eagle, Haliaeetus leucocephalus +vulture +great grey owl, great gray owl, Strix nebulosa +European fire salamander, Salamandra salamandra +common newt, Triturus vulgaris +eft +spotted salamander, Ambystoma maculatum +axolotl, mud puppy, Ambystoma mexicanum +bullfrog, Rana catesbeiana +tree frog, tree-frog +tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui +loggerhead, loggerhead turtle, Caretta caretta +leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea +mud turtle +terrapin +box turtle, box tortoise +banded gecko +common iguana, iguana, Iguana iguana +American chameleon, anole, Anolis carolinensis +whiptail, whiptail lizard +agama +frilled lizard, Chlamydosaurus kingi +alligator lizard +Gila monster, Heloderma suspectum +green lizard, Lacerta viridis +African chameleon, Chamaeleo chamaeleon +Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis +African crocodile, Nile crocodile, Crocodylus niloticus +American alligator, Alligator mississipiensis +triceratops +thunder snake, worm snake, Carphophis amoenus +ringneck snake, ring-necked snake, ring snake +hognose snake, puff adder, sand viper +green snake, grass snake +king snake, kingsnake +garter snake, grass snake +water snake +vine snake +night snake, Hypsiglena torquata +boa constrictor, Constrictor constrictor +rock python, rock snake, Python sebae +Indian cobra, Naja naja +green mamba +sea snake +horned viper, cerastes, sand viper, horned asp, Cerastes cornutus +diamondback, diamondback rattlesnake, Crotalus adamanteus +sidewinder, horned rattlesnake, Crotalus cerastes +trilobite +harvestman, daddy longlegs, Phalangium opilio +scorpion +black and gold garden spider, Argiope aurantia +barn spider, Araneus cavaticus +garden spider, Aranea diademata +black widow, Latrodectus mactans +tarantula +wolf spider, hunting spider +tick +centipede +black grouse +ptarmigan +ruffed grouse, partridge, Bonasa umbellus +prairie chicken, prairie grouse, prairie fowl +peacock +quail +partridge +African grey, African gray, Psittacus erithacus +macaw +sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita +lorikeet +coucal +bee eater +hornbill +hummingbird +jacamar +toucan +drake +red-breasted merganser, Mergus serrator +goose +black swan, Cygnus atratus +tusker +echidna, spiny anteater, anteater +platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus +wallaby, brush kangaroo +koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus +wombat +jellyfish +sea anemone, anemone +brain coral +flatworm, platyhelminth +nematode, nematode worm, roundworm +conch +snail +slug +sea slug, nudibranch +chiton, coat-of-mail shell, sea cradle, polyplacophore +chambered nautilus, pearly nautilus, nautilus +Dungeness crab, Cancer magister +rock crab, Cancer irroratus +fiddler crab +king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica +American lobster, Northern lobster, Maine lobster, Homarus americanus +spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish +crayfish, crawfish, crawdad, crawdaddy +hermit crab +isopod +white stork, Ciconia ciconia +black stork, Ciconia nigra +spoonbill +flamingo +little blue heron, Egretta caerulea +American egret, great white heron, Egretta albus +bittern +crane +limpkin, Aramus pictus +European gallinule, Porphyrio porphyrio +American coot, marsh hen, mud hen, water hen, Fulica americana +bustard +ruddy turnstone, Arenaria interpres +red-backed sandpiper, dunlin, Erolia alpina +redshank, Tringa totanus +dowitcher +oystercatcher, oyster catcher +pelican +king penguin, Aptenodytes patagonica +albatross, mollymawk +grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus +killer whale, killer, orca, grampus, sea wolf, Orcinus orca +dugong, Dugong dugon +sea lion +Chihuahua +Japanese spaniel +Maltese dog, Maltese terrier, Maltese +Pekinese, Pekingese, Peke +Shih-Tzu +Blenheim spaniel +papillon +toy terrier +Rhodesian ridgeback +Afghan hound, Afghan +basset, basset hound +beagle +bloodhound, sleuthhound +bluetick +black-and-tan coonhound +Walker hound, Walker foxhound +English foxhound +redbone +borzoi, Russian wolfhound +Irish wolfhound +Italian greyhound +whippet +Ibizan hound, Ibizan Podenco +Norwegian elkhound, elkhound +otterhound, otter hound +Saluki, gazelle hound +Scottish deerhound, deerhound +Weimaraner +Staffordshire bullterrier, Staffordshire bull terrier +American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier +Bedlington terrier +Border terrier +Kerry blue terrier +Irish terrier +Norfolk terrier +Norwich terrier +Yorkshire terrier +wire-haired fox terrier +Lakeland terrier +Sealyham terrier, Sealyham +Airedale, Airedale terrier +cairn, cairn terrier +Australian terrier +Dandie Dinmont, Dandie Dinmont terrier +Boston bull, Boston terrier +miniature schnauzer +giant schnauzer +standard schnauzer +Scotch terrier, Scottish terrier, Scottie +Tibetan terrier, chrysanthemum dog +silky terrier, Sydney silky +soft-coated wheaten terrier +West Highland white terrier +Lhasa, Lhasa apso +flat-coated retriever +curly-coated retriever +golden retriever +Labrador retriever +Chesapeake Bay retriever +German short-haired pointer +vizsla, Hungarian pointer +English setter +Irish setter, red setter +Gordon setter +Brittany spaniel +clumber, clumber spaniel +English springer, English springer spaniel +Welsh springer spaniel +cocker spaniel, English cocker spaniel, cocker +Sussex spaniel +Irish water spaniel +kuvasz +schipperke +groenendael +malinois +briard +kelpie +komondor +Old English sheepdog, bobtail +Shetland sheepdog, Shetland sheep dog, Shetland +collie +Border collie +Bouvier des Flandres, Bouviers des Flandres +Rottweiler +German shepherd, German shepherd dog, German police dog, alsatian +Doberman, Doberman pinscher +miniature pinscher +Greater Swiss Mountain dog +Bernese mountain dog +Appenzeller +EntleBucher +boxer +bull mastiff +Tibetan mastiff +French bulldog +Great Dane +Saint Bernard, St Bernard +Eskimo dog, husky +malamute, malemute, Alaskan malamute +Siberian husky +dalmatian, coach dog, carriage dog +affenpinscher, monkey pinscher, monkey dog +basenji +pug, pug-dog +Leonberg +Newfoundland, Newfoundland dog +Great Pyrenees +Samoyed, Samoyede +Pomeranian +chow, chow chow +keeshond +Brabancon griffon +Pembroke, Pembroke Welsh corgi +Cardigan, Cardigan Welsh corgi +toy poodle +miniature poodle +standard poodle +Mexican hairless +timber wolf, grey wolf, gray wolf, Canis lupus +white wolf, Arctic wolf, Canis lupus tundrarum +red wolf, maned wolf, Canis rufus, Canis niger +coyote, prairie wolf, brush wolf, Canis latrans +dingo, warrigal, warragal, Canis dingo +dhole, Cuon alpinus +African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus +hyena, hyaena +red fox, Vulpes vulpes +kit fox, Vulpes macrotis +Arctic fox, white fox, Alopex lagopus +grey fox, gray fox, Urocyon cinereoargenteus +tabby, tabby cat +tiger cat +Persian cat +Siamese cat, Siamese +Egyptian cat +cougar, puma, catamount, mountain lion, painter, panther, Felis concolor +lynx, catamount +leopard, Panthera pardus +snow leopard, ounce, Panthera uncia +jaguar, panther, Panthera onca, Felis onca +lion, king of beasts, Panthera leo +tiger, Panthera tigris +cheetah, chetah, Acinonyx jubatus +brown bear, bruin, Ursus arctos +American black bear, black bear, Ursus americanus, Euarctos americanus +ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus +sloth bear, Melursus ursinus, Ursus ursinus +mongoose +meerkat, mierkat +tiger beetle +ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle +ground beetle, carabid beetle +long-horned beetle, longicorn, longicorn beetle +leaf beetle, chrysomelid +dung beetle +rhinoceros beetle +weevil +fly +bee +ant, emmet, pismire +grasshopper, hopper +cricket +walking stick, walkingstick, stick insect +cockroach, roach +mantis, mantid +cicada, cicala +leafhopper +lacewing, lacewing fly +dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk +damselfly +admiral +ringlet, ringlet butterfly +monarch, monarch butterfly, milkweed butterfly, Danaus plexippus +cabbage butterfly +sulphur butterfly, sulfur butterfly +lycaenid, lycaenid butterfly +starfish, sea star +sea urchin +sea cucumber, holothurian +wood rabbit, cottontail, cottontail rabbit +hare +Angora, Angora rabbit +hamster +porcupine, hedgehog +fox squirrel, eastern fox squirrel, Sciurus niger +marmot +beaver +guinea pig, Cavia cobaya +sorrel +zebra +hog, pig, grunter, squealer, Sus scrofa +wild boar, boar, Sus scrofa +warthog +hippopotamus, hippo, river horse, Hippopotamus amphibius +ox +water buffalo, water ox, Asiatic buffalo, Bubalus bubalis +bison +ram, tup +bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis +ibex, Capra ibex +hartebeest +impala, Aepyceros melampus +gazelle +Arabian camel, dromedary, Camelus dromedarius +llama +weasel +mink +polecat, fitch, foulmart, foumart, Mustela putorius +black-footed ferret, ferret, Mustela nigripes +otter +skunk, polecat, wood pussy +badger +armadillo +three-toed sloth, ai, Bradypus tridactylus +orangutan, orang, orangutang, Pongo pygmaeus +gorilla, Gorilla gorilla +chimpanzee, chimp, Pan troglodytes +gibbon, Hylobates lar +siamang, Hylobates syndactylus, Symphalangus syndactylus +guenon, guenon monkey +patas, hussar monkey, Erythrocebus patas +baboon +macaque +langur +colobus, colobus monkey +proboscis monkey, Nasalis larvatus +marmoset +capuchin, ringtail, Cebus capucinus +howler monkey, howler +titi, titi monkey +spider monkey, Ateles geoffroyi +squirrel monkey, Saimiri sciureus +Madagascar cat, ring-tailed lemur, Lemur catta +indri, indris, Indri indri, Indri brevicaudatus +Indian elephant, Elephas maximus +African elephant, Loxodonta africana +lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens +giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca +barracouta, snoek +eel +coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch +rock beauty, Holocanthus tricolor +anemone fish +sturgeon +gar, garfish, garpike, billfish, Lepisosteus osseus +lionfish +puffer, pufferfish, blowfish, globefish +abacus +abaya +academic gown, academic robe, judge's robe +accordion, piano accordion, squeeze box +acoustic guitar +aircraft carrier, carrier, flattop, attack aircraft carrier +airliner +airship, dirigible +altar +ambulance +amphibian, amphibious vehicle +analog clock +apiary, bee house +apron +ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin +assault rifle, assault gun +backpack, back pack, knapsack, packsack, rucksack, haversack +bakery, bakeshop, bakehouse +balance beam, beam +balloon +ballpoint, ballpoint pen, ballpen, Biro +Band Aid +banjo +bannister, banister, balustrade, balusters, handrail +barbell +barber chair +barbershop +barn +barometer +barrel, cask +barrow, garden cart, lawn cart, wheelbarrow +baseball +basketball +bassinet +bassoon +bathing cap, swimming cap +bath towel +bathtub, bathing tub, bath, tub +beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon +beacon, lighthouse, beacon light, pharos +beaker +bearskin, busby, shako +beer bottle +beer glass +bell cote, bell cot +bib +bicycle-built-for-two, tandem bicycle, tandem +bikini, two-piece +binder, ring-binder +binoculars, field glasses, opera glasses +birdhouse +boathouse +bobsled, bobsleigh, bob +bolo tie, bolo, bola tie, bola +bonnet, poke bonnet +bookcase +bookshop, bookstore, bookstall +bottlecap +bow +bow tie, bow-tie, bowtie +brass, memorial tablet, plaque +brassiere, bra, bandeau +breakwater, groin, groyne, mole, bulwark, seawall, jetty +breastplate, aegis, egis +broom +bucket, pail +buckle +bulletproof vest +bullet train, bullet +butcher shop, meat market +cab, hack, taxi, taxicab +caldron, cauldron +candle, taper, wax light +cannon +canoe +can opener, tin opener +cardigan +car mirror +carousel, carrousel, merry-go-round, roundabout, whirligig +carpenter's kit, tool kit +carton +car wheel +cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM +cassette +cassette player +castle +catamaran +CD player +cello, violoncello +cellular telephone, cellular phone, cellphone, cell, mobile phone +chain +chainlink fence +chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour +chain saw, chainsaw +chest +chiffonier, commode +chime, bell, gong +china cabinet, china closet +Christmas stocking +church, church building +cinema, movie theater, movie theatre, movie house, picture palace +cleaver, meat cleaver, chopper +cliff dwelling +cloak +clog, geta, patten, sabot +cocktail shaker +coffee mug +coffeepot +coil, spiral, volute, whorl, helix +combination lock +computer keyboard, keypad +confectionery, confectionary, candy store +container ship, containership, container vessel +convertible +corkscrew, bottle screw +cornet, horn, trumpet, trump +cowboy boot +cowboy hat, ten-gallon hat +cradle +crane +crash helmet +crate +crib, cot +Crock Pot +croquet ball +crutch +cuirass +dam, dike, dyke +desk +desktop computer +dial telephone, dial phone +diaper, nappy, napkin +digital clock +digital watch +dining table, board +dishrag, dishcloth +dishwasher, dish washer, dishwashing machine +disk brake, disc brake +dock, dockage, docking facility +dogsled, dog sled, dog sleigh +dome +doormat, welcome mat +drilling platform, offshore rig +drum, membranophone, tympan +drumstick +dumbbell +Dutch oven +electric fan, blower +electric guitar +electric locomotive +entertainment center +envelope +espresso maker +face powder +feather boa, boa +file, file cabinet, filing cabinet +fireboat +fire engine, fire truck +fire screen, fireguard +flagpole, flagstaff +flute, transverse flute +folding chair +football helmet +forklift +fountain +fountain pen +four-poster +freight car +French horn, horn +frying pan, frypan, skillet +fur coat +garbage truck, dustcart +gasmask, respirator, gas helmet +gas pump, gasoline pump, petrol pump, island dispenser +goblet +go-kart +golf ball +golfcart, golf cart +gondola +gong, tam-tam +gown +grand piano, grand +greenhouse, nursery, glasshouse +grille, radiator grille +grocery store, grocery, food market, market +guillotine +hair slide +hair spray +half track +hammer +hamper +hand blower, blow dryer, blow drier, hair dryer, hair drier +hand-held computer, hand-held microcomputer +handkerchief, hankie, hanky, hankey +hard disc, hard disk, fixed disk +harmonica, mouth organ, harp, mouth harp +harp +harvester, reaper +hatchet +holster +home theater, home theatre +honeycomb +hook, claw +hoopskirt, crinoline +horizontal bar, high bar +horse cart, horse-cart +hourglass +iPod +iron, smoothing iron +jack-o'-lantern +jean, blue jean, denim +jeep, landrover +jersey, T-shirt, tee shirt +jigsaw puzzle +jinrikisha, ricksha, rickshaw +joystick +kimono +knee pad +knot +lab coat, laboratory coat +ladle +lampshade, lamp shade +laptop, laptop computer +lawn mower, mower +lens cap, lens cover +letter opener, paper knife, paperknife +library +lifeboat +lighter, light, igniter, ignitor +limousine, limo +liner, ocean liner +lipstick, lip rouge +Loafer +lotion +loudspeaker, speaker, speaker unit, loudspeaker system, speaker system +loupe, jeweler's loupe +lumbermill, sawmill +magnetic compass +mailbag, postbag +mailbox, letter box +maillot +maillot, tank suit +manhole cover +maraca +marimba, xylophone +mask +matchstick +maypole +maze, labyrinth +measuring cup +medicine chest, medicine cabinet +megalith, megalithic structure +microphone, mike +microwave, microwave oven +military uniform +milk can +minibus +miniskirt, mini +minivan +missile +mitten +mixing bowl +mobile home, manufactured home +Model T +modem +monastery +monitor +moped +mortar +mortarboard +mosque +mosquito net +motor scooter, scooter +mountain bike, all-terrain bike, off-roader +mountain tent +mouse, computer mouse +mousetrap +moving van +muzzle +nail +neck brace +necklace +nipple +notebook, notebook computer +obelisk +oboe, hautboy, hautbois +ocarina, sweet potato +odometer, hodometer, mileometer, milometer +oil filter +organ, pipe organ +oscilloscope, scope, cathode-ray oscilloscope, CRO +overskirt +oxcart +oxygen mask +packet +paddle, boat paddle +paddlewheel, paddle wheel +padlock +paintbrush +pajama, pyjama, pj's, jammies +palace +panpipe, pandean pipe, syrinx +paper towel +parachute, chute +parallel bars, bars +park bench +parking meter +passenger car, coach, carriage +patio, terrace +pay-phone, pay-station +pedestal, plinth, footstall +pencil box, pencil case +pencil sharpener +perfume, essence +Petri dish +photocopier +pick, plectrum, plectron +pickelhaube +picket fence, paling +pickup, pickup truck +pier +piggy bank, penny bank +pill bottle +pillow +ping-pong ball +pinwheel +pirate, pirate ship +pitcher, ewer +plane, carpenter's plane, woodworking plane +planetarium +plastic bag +plate rack +plow, plough +plunger, plumber's helper +Polaroid camera, Polaroid Land camera +pole +police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria +poncho +pool table, billiard table, snooker table +pop bottle, soda bottle +pot, flowerpot +potter's wheel +power drill +prayer rug, prayer mat +printer +prison, prison house +projectile, missile +projector +puck, hockey puck +punching bag, punch bag, punching ball, punchball +purse +quill, quill pen +quilt, comforter, comfort, puff +racer, race car, racing car +racket, racquet +radiator +radio, wireless +radio telescope, radio reflector +rain barrel +recreational vehicle, RV, R.V. +reel +reflex camera +refrigerator, icebox +remote control, remote +restaurant, eating house, eating place, eatery +revolver, six-gun, six-shooter +rifle +rocking chair, rocker +rotisserie +rubber eraser, rubber, pencil eraser +rugby ball +rule, ruler +running shoe +safe +safety pin +saltshaker, salt shaker +sandal +sarong +sax, saxophone +scabbard +scale, weighing machine +school bus +schooner +scoreboard +screen, CRT screen +screw +screwdriver +seat belt, seatbelt +sewing machine +shield, buckler +shoe shop, shoe-shop, shoe store +shoji +shopping basket +shopping cart +shovel +shower cap +shower curtain +ski +ski mask +sleeping bag +slide rule, slipstick +sliding door +slot, one-armed bandit +snorkel +snowmobile +snowplow, snowplough +soap dispenser +soccer ball +sock +solar dish, solar collector, solar furnace +sombrero +soup bowl +space bar +space heater +space shuttle +spatula +speedboat +spider web, spider's web +spindle +sports car, sport car +spotlight, spot +stage +steam locomotive +steel arch bridge +steel drum +stethoscope +stole +stone wall +stopwatch, stop watch +stove +strainer +streetcar, tram, tramcar, trolley, trolley car +stretcher +studio couch, day bed +stupa, tope +submarine, pigboat, sub, U-boat +suit, suit of clothes +sundial +sunglass +sunglasses, dark glasses, shades +sunscreen, sunblock, sun blocker +suspension bridge +swab, swob, mop +sweatshirt +swimming trunks, bathing trunks +swing +switch, electric switch, electrical switch +syringe +table lamp +tank, army tank, armored combat vehicle, armoured combat vehicle +tape player +teapot +teddy, teddy bear +television, television system +tennis ball +thatch, thatched roof +theater curtain, theatre curtain +thimble +thresher, thrasher, threshing machine +throne +tile roof +toaster +tobacco shop, tobacconist shop, tobacconist +toilet seat +torch +totem pole +tow truck, tow car, wrecker +toyshop +tractor +trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi +tray +trench coat +tricycle, trike, velocipede +trimaran +tripod +triumphal arch +trolleybus, trolley coach, trackless trolley +trombone +tub, vat +turnstile +typewriter keyboard +umbrella +unicycle, monocycle +upright, upright piano +vacuum, vacuum cleaner +vase +vault +velvet +vending machine +vestment +viaduct +violin, fiddle +volleyball +waffle iron +wall clock +wallet, billfold, notecase, pocketbook +wardrobe, closet, press +warplane, military plane +washbasin, handbasin, washbowl, lavabo, wash-hand basin +washer, automatic washer, washing machine +water bottle +water jug +water tower +whiskey jug +whistle +wig +window screen +window shade +Windsor tie +wine bottle +wing +wok +wooden spoon +wool, woolen, woollen +worm fence, snake fence, snake-rail fence, Virginia fence +wreck +yawl +yurt +web site, website, internet site, site +comic book +crossword puzzle, crossword +street sign +traffic light, traffic signal, stoplight +book jacket, dust cover, dust jacket, dust wrapper +menu +plate +guacamole +consomme +hot pot, hotpot +trifle +ice cream, icecream +ice lolly, lolly, lollipop, popsicle +French loaf +bagel, beigel +pretzel +cheeseburger +hotdog, hot dog, red hot +mashed potato +head cabbage +broccoli +cauliflower +zucchini, courgette +spaghetti squash +acorn squash +butternut squash +cucumber, cuke +artichoke, globe artichoke +bell pepper +cardoon +mushroom +Granny Smith +strawberry +orange +lemon +fig +pineapple, ananas +banana +jackfruit, jak, jack +custard apple +pomegranate +hay +carbonara +chocolate sauce, chocolate syrup +dough +meat loaf, meatloaf +pizza, pizza pie +potpie +burrito +red wine +espresso +cup +eggnog +alp +bubble +cliff, drop, drop-off +coral reef +geyser +lakeside, lakeshore +promontory, headland, head, foreland +sandbar, sand bar +seashore, coast, seacoast, sea-coast +valley, vale +volcano +ballplayer, baseball player +groom, bridegroom +scuba diver +rapeseed +daisy +yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum +corn +acorn +hip, rose hip, rosehip +buckeye, horse chestnut, conker +coral fungus +agaric +gyromitra +stinkhorn, carrion fungus +earthstar +hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa +bolete +ear, spike, capitulum +toilet tissue, toilet paper, bathroom tissue diff --git a/PyTorch-to-TensorFlow-Model-Conversion/requirements.txt b/PyTorch-to-TensorFlow-Model-Conversion/requirements.txt new file mode 100644 index 000000000..ed932d228 --- /dev/null +++ b/PyTorch-to-TensorFlow-Model-Conversion/requirements.txt @@ -0,0 +1,7 @@ +albumentations==0.4.5 +opencv-python>=3.4.1.15 +# for FullyConvolutionalResnet18 +pytorch2keras==0.2.4 +tensorflow==2.1.0 +torch==1.4 +torchvision==0.5.0 \ No newline at end of file diff --git a/README.md b/README.md index e41b41dfd..34f4d1c4c 100644 --- a/README.md +++ b/README.md @@ -13,6 +13,7 @@ Want to become an expert in AI? [AI Courses by OpenCV](https://opencv.org/course | Blog Post | | | ------------- |:-------------| +|[PyTorch to Tensorflow Model Conversion](https://www.learnopencv.com/pytorch-to-tensorflow-model-conversion/) | [Code](https://github.com/spmallick/learnopencv/tree/master/PyTorch-to-TensorFlow-Model-Conversion) | |[Snake Game with OpenCV Python](https://www.learnopencv.com/snake-game-with-opencv-python/)|[Code](https://github.com/spmallick/learnopencv/tree/master/SnakeGame)| |[Stanford MRNet Challenge: Classifying Knee MRIs](https://www.learnopencv.com/stanford-mrnet-challenge-classifying-knee-mris/)|[Code](https://github.com/spmallick/learnopencv/tree/master/MRNet-Single-Model)| |[Experiment Logging with TensorBoard and wandb](https://www.learnopencv.com/experiment-logging-with-tensorboard-and-wandb)|[Code](https://github.com/spmallick/learnopencv/tree/master/PyTorch-Vision-Experiment-Logging)|