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import gradio as gr
import pandas as pd
import torch
import torchvision.transforms as transforms
from PIL import Image
import lightning as L
from src.models.classifier import ImageNetClassifier
# Define the class names (replace with your actual class names)
# Add your dog breed classes here
# Example:
# "Labrador", "German Shepherd", "Golden Retriever", etc.
class_names = [
"n01443537", "n01828970", "n02093859", "n02115913", "n02480495", "n02879718", "n03272562", "n03710637", "n03961711", "n04310018" "n04599235"
"n01440764", "n01824575", "n02093754", "n02115641", "n02457408", "n02877765", "n03272010", "n03710193", "n03958227", "n04296562" "n04597913"
"n01484850", "n01829413", "n02093991", "n02116738", "n02480855", "n02883205", "n03290653", "n03710721", "n03967562", "n04311004" "n04604644"
"n01491361", "n01833805", "n02094114", "n02117135", "n02481823", "n02892201", "n03291819", "n03717622", "n03970156", "n04311174" "n04606251"
"n01494475", "n01843065", "n02094258", "n02119022", "n02483362", "n02892767", "n03297495", "n03720891", "n03976467", "n04317175" "n04612504"
"n01496331", "n01843383", "n02094433", "n02119789", "n02483708", "n02894605", "n03314780", "n03721384", "n03976657", "n04325704" "n04613696"
"n01498041", "n01847000", "n02095314", "n02120079", "n02484975", "n02895154", "n03325584", "n03724870", "n03977966", "n04326547" "n06359193"
"n01514668", "n01855032", "n02095570", "n02120505", "n02486261", "n02906734", "n03337140", "n03729826", "n03980874", "n04328186" "n06596364"
"n01514859", "n01855672", "n02095889", "n02123045", "n02486410", "n02909870", "n03344393", "n03733131", "n03982430", "n04330267" "n06785654"
"n01518878", "n01860187", "n02096051", "n02123159", "n02487347", "n02910353", "n03345487", "n03733281", "n03983396", "n04332243" "n06794110"
"n01530575", "n01871265", "n02096177", "n02123394", "n02488291", "n02916936", "n03347037", "n03733805", "n03991062", "n04335435" "n06874185"
"n01531178", "n01872401", "n02096294", "n02123597", "n02488702", "n02917067", "n03355925", "n03742115", "n03992509", "n04336792" "n07248320"
"n01532829", "n01873310", "n02096437", "n02124075", "n02489166", "n02927161", "n03372029", "n03743016", "n03995372", "n04344873" "n07565083"
"n01534433", "n01877812", "n02096585", "n02125311", "n02490219", "n02930766", "n03376595", "n03759954", "n03998194", "n04346328" "n07579787"
"n01537544", "n01882714", "n02097047", "n02127052", "n02492035", "n02939185", "n03379051", "n03761084", "n04004767", "n04347754" "n07583066"
"n01558993", "n01883070", "n02097130", "n02128385", "n02492660", "n02948072", "n03384352", "n03763968", "n04005630", "n04350905" "n07584110"
"n01560419", "n01910747", "n02097209", "n02128757", "n02493509", "n02950826", "n03388043", "n03764736", "n04008634", "n04355338" "n07590611"
"n01580077", "n01914609", "n02097298", "n02128925", "n02493793", "n02951358", "n03388183", "n03769881", "n04009552", "n04355933" "n07613480"
"n01582220", "n01917289", "n02097474", "n02129165", "n02494079", "n02951585", "n03388549", "n03770439", "n04019541", "n04356056" "n07614500"
"n01592084", "n01924916", "n02097658", "n02129604", "n02497673", "n02963159", "n03393912", "n03770679", "n04023962", "n04357314" "n07615774"
"n01601694", "n01930112", "n02098105", "n02130308", "n02500267", "n02965783", "n03394916", "n03773504", "n04026417", "n04366367" "n07684084"
"n01608432", "n01943899", "n02098286", "n02132136", "n02504013", "n02966193", "n03400231", "n03775071", "n04033901", "n04367480" "n07693725"
"n01614925", "n01944390", "n02098413", "n02133161", "n02504458", "n02966687", "n03404251", "n03775546", "n04033995", "n04370456" "n07695742"
"n01616318", "n01945685", "n02099267", "n02134084", "n02509815", "n02971356", "n03417042", "n03776460", "n04037443", "n04371430" "n07697313"
"n01622779", "n01950731", "n02099429", "n02134418", "n02510455", "n02974003", "n03424325", "n03777568", "n04039381", "n04371774" "n07697537"
"n01629819", "n01955084", "n02099601", "n02137549", "n02514041", "n02977058", "n03425413", "n03777754", "n04040759", "n04372370" "n07711569"
"n01630670", "n01968897", "n02099712", "n02138441", "n02526121", "n02978881", "n03443371", "n03781244", "n04041544", "n04376876" "n07714571"
"n01631663", "n01978287", "n02099849", "n02165105", "n02536864", "n02979186", "n03444034", "n03782006", "n04044716", "n04380533" "n07714990"
"n01632458", "n01978455", "n02100236", "n02165456", "n02606052", "n02980441", "n03445777", "n03785016", "n04049303", "n04389033" "n07715103"
"n01632777", "n01980166", "n02100583", "n02167151", "n02607072", "n02981792", "n03445924", "n03786901", "n04065272", "n04392985" "n07716358"
"n01641577", "n01981276", "n02100735", "n02168699", "n02640242", "n02988304", "n03447447", "n03787032", "n04067472", "n04398044" "n07716906"
"n01644373", "n01983481", "n02100877", "n02169497", "n02641379", "n02992211", "n03447721", "n03788195", "n04069434", "n04399382" "n07717410"
"n01644900", "n01984695", "n02101006", "n02172182", "n02643566", "n02992529", "n03450230", "n03788365", "n04070727", "n04404412" "n07717556"
"n01664065", "n01985128", "n02101388", "n02174001", "n02655020", "n02999410", "n03452741", "n03791053", "n04074963", "n04409515" "n07718472"
"n01665541", "n01986214", "n02101556", "n02177972", "n02666196", "n03000134", "n03457902", "n03792782", "n04081281", "n04417672" "n07718747"
"n01667114", "n01990800", "n02102040", "n02190166", "n02667093", "n03000247", "n03459775", "n03792972", "n04086273", "n04418357" "n07720875"
"n01667778", "n02002556", "n02102177", "n02206856", "n02669723", "n03000684", "n03461385", "n03793489", "n04090263", "n04423845" "n07730033"
"n01669191", "n02002724", "n02102318", "n02219486", "n02672831", "n03014705", "n03467068", "n03794056", "n04099969", "n04428191" "n07734744"
"n01675722", "n02006656", "n02102480", "n02226429", "n02676566", "n03016953", "n03476684", "n03796401", "n04111531", "n04429376" "n07742313"
"n01677366", "n02007558", "n02102973", "n02229544", "n02687172", "n03017168", "n03476991", "n03803284", "n04116512", "n04435653" "n07745940"
"n01682714", "n02009229", "n02104029", "n02231487", "n02690373", "n03018349", "n03478589", "n03804744", "n04118538", "n04442312" "n07747607"
"n01685808", "n02009912", "n02104365", "n02233338", "n02692877", "n03026506", "n03481172", "n03814639", "n04118776", "n04443257" "n07749582"
"n01687978", "n02011460", "n02105056", "n02236044", "n02699494", "n03028079", "n03482405", "n03814906", "n04120489", "n04447861" "n07753113"
"n01688243", "n02012849", "n02105162", "n02256656", "n02701002", "n03032252", "n03483316", "n03825788", "n04125021", "n04456115" "n07753275"
"n01689811", "n02013706", "n02105251", "n02259212", "n02704792", "n03041632", "n03485407", "n03832673", "n04127249", "n04458633" "n07753592"
"n01692333", "n02017213", "n02105412", "n02264363", "n02708093", "n03042490", "n03485794", "n03837869", "n04131690", "n04461696" "n07754684"
"n01693334", "n02018207", "n02105505", "n02268443", "n02727426", "n03045698", "n03492542", "n03838899", "n04133789", "n04462240" "n07760859"
"n01694178", "n02018795", "n02105641", "n02268853", "n02730930", "n03047690", "n03494278", "n03840681", "n04136333", "n04465501" "n07768694"
"n01695060", "n02025239", "n02105855", "n02276258", "n02747177", "n03062245", "n03495258", "n03841143", "n04141076", "n04467665" "n07802026"
"n01697457", "n02027492", "n02106030", "n02277742", "n02749479", "n03063599", "n03496892", "n03843555", "n04141327", "n04476259" "n07831146"
"n01698640", "n02028035", "n02106166", "n02279972", "n02769748", "n03063689", "n03498962", "n03854065", "n04141975", "n04479046" "n07836838"
"n01704323", "n02033041", "n02106382", "n02280649", "n02776631", "n03065424", "n03527444", "n03857828", "n04146614", "n04482393" "n07860988"
"n01728572", "n02037110", "n02106550", "n02281406", "n02777292", "n03075370", "n03529860", "n03866082", "n04147183", "n04483307" "n07871810"
"n01728920", "n02051845", "n02106662", "n02281787", "n02782093", "n03085013", "n03530642", "n03868242", "n04149813", "n04485082" "n07873807"
"n01729322", "n02056570", "n02107142", "n02317335", "n02783161", "n03089624", "n03532672", "n03868863", "n04152593", "n04486054" "n07875152"
"n01729977", "n02058221", "n02107312", "n02319095", "n02786058", "n03095699", "n03534580", "n03871628", "n04153751", "n04487081" "n07880968"
"n01734418", "n02066245", "n02107574", "n02321529", "n02787622", "n03100240", "n03535780", "n03873416", "n04154565", "n04487394" "n07892512"
"n01735189", "n02071294", "n02107683", "n02325366", "n02788148", "n03109150", "n03538406", "n03874293", "n04162706", "n04493381" "n07920052"
"n01737021", "n02074367", "n02107908", "n02326432", "n02790996", "n03110669", "n03544143", "n03874599", "n04179913", "n04501370" "n07930864"
"n01739381", "n02077923", "n02108000", "n02328150", "n02791124", "n03124043", "n03584254", "n03876231", "n04192698", "n04505470" "n07932039"
"n01740131", "n02085620", "n02108089", "n02342885", "n02791270", "n03124170", "n03584829", "n03877472", "n04200800", "n04507155" "n09193705"
"n01742172", "n02085782", "n02108422", "n02346627", "n02793495", "n03125729", "n03590841", "n03877845", "n04201297", "n04509417" "n09229709"
"n01744401", "n02085936", "n02108551", "n02356798", "n02794156", "n03126707", "n03594734", "n03884397", "n04204238", "n04515003" "n09246464"
"n01748264", "n02086079", "n02108915", "n02361337", "n02795169", "n03127747", "n03594945", "n03887697", "n04204347", "n04517823" "n09256479"
"n01749939", "n02086240", "n02109047", "n02363005", "n02797295", "n03127925", "n03595614", "n03888257", "n04208210", "n04522168" "n09288635"
"n01751748", "n02086646", "n02109525", "n02364673", "n02799071", "n03131574", "n03598930", "n03888605", "n04209133", "n04523525" "n09332890"
"n01753488", "n02086910", "n02109961", "n02389026", "n02802426", "n03133878", "n03599486", "n03891251", "n04209239", "n04525038" "n09399592"
"n01755581", "n02087046", "n02110063", "n02391049", "n02804414", "n03134739", "n03602883", "n03891332", "n04228054", "n04525305" "n09421951"
"n01756291", "n02087394", "n02110185", "n02395406", "n02804610", "n03141823", "n03617480", "n03895866", "n04229816", "n04532106" "n09428293"
"n01768244", "n02088094", "n02110341", "n02396427", "n02807133", "n03146219", "n03623198", "n03899768", "n04235860", "n04532670" "n09468604"
"n01770081", "n02088238", "n02110627", "n02397096", "n02808304", "n03160309", "n03627232", "n03902125", "n04238763", "n04536866" "n09472597"
"n01770393", "n02088364", "n02110806", "n02398521", "n02808440", "n03179701", "n03630383", "n03903868", "n04239074", "n04540053" "n09835506"
"n01773157", "n02088466", "n02110958", "n02403003", "n02814533", "n03180011", "n03633091", "n03908618", "n04243546", "n04542943" "n10148035"
"n01773549", "n02088632", "n02111129", "n02408429", "n02814860", "n03187595", "n03637318", "n03908714", "n04251144", "n04548280" "n10565667"
"n01773797", "n02089078", "n02111277", "n02410509", "n02815834", "n03188531", "n03642806", "n03916031", "n04252077", "n04548362" "n11879895"
"n01774384", "n02089867", "n02111500", "n02412080", "n02817516", "n03196217", "n03649909", "n03920288", "n04252225", "n04550184" "n11939491"
"n01774750", "n02089973", "n02111889", "n02415577", "n02823428", "n03197337", "n03657121", "n03924679", "n04254120", "n04552348" "n12057211"
"n01775062", "n02090379", "n02112018", "n02417914", "n02823750", "n03201208", "n03658185", "n03929660", "n04254680", "n04553703" "n12144580"
"n01776313", "n02090622", "n02112137", "n02422106", "n02825657", "n03207743", "n03661043", "n03929855", "n04254777", "n04554684" "n12267677"
"n01784675", "n02090721", "n02112350", "n02422699", "n02834397", "n03207941", "n03662601", "n03930313", "n04258138", "n04557648" "n12620546"
"n01795545", "n02091032", "n02112706", "n02423022", "n02835271", "n03208938", "n03666591", "n03930630", "n04259630", "n04560804" "n12768682"
"n01796340", "n02091134", "n02113023", "n02437312", "n02837789", "n03216828", "n03670208", "n03933933", "n04263257", "n04562935" "n12985857"
"n01797886", "n02091244", "n02113186", "n02437616", "n02840245", "n03218198", "n03673027", "n03935335", "n04264628", "n04579145" "n12998815"
"n01798484", "n02091467", "n02113624", "n02441942", "n02841315", "n03220513", "n03676483", "n03937543", "n04265275", "n04579432" "n13037406"
"n01806143", "n02091635", "n02113712", "n02442845", "n02843684", "n03223299", "n03680355", "n03938244", "n04266014", "n04584207" "n13040303"
"n01806567", "n02091831", "n02113799", "n02443114", "n02859443", "n03240683", "n03690938", "n03942813", "n04270147", "n04589890" "n13044778"
"n01807496", "n02092002", "n02113978", "n02443484", "n02860847", "n03249569", "n03691459", "n03944341", "n04273569", "n04590129" "n13052670"
"n01817953", "n02092339", "n02114367", "n02444819", "n02865351", "n03250847", "n03692522", "n03947888", "n04275548", "n04591157" "n13054560"
"n01818515", "n02093256", "n02114548", "n02445715", "n02869837", "n03255030", "n03697007", "n03950228", "n04277352", "n04591713" "n13133613"
"n01819313", "n02093428", "n02114712", "n02447366", "n02870880", "n03259280", "n03706229", "n03954731", "n04285008", "n04592741" "n15075141"
"n01820546", "n02093647", "n02114855", "n02454379", "n02871525", "n03271574", "n03709823", "n03956157", "n04286575", "n04596742"]
mapping_file = 'LOC_synset_mapping.txt'
mapping_file_df = pd.read_csv(mapping_file, header = None, sep =':')
mapping_file_dict = dict(zip(mapping_file_df.iloc[:, 0].str.strip(), mapping_file_df.iloc[:, 1].str.strip()))
class_names_dict = {'n01440764': 0, 'n01443537': 1, 'n01484850': 2, 'n01491361': 3, 'n01494475': 4, 'n01496331': 5, 'n01498041': 6, 'n01514668': 7, 'n01514859': 8
, 'n01518878': 9, 'n01530575': 10, 'n01531178': 11, 'n01532829': 12, 'n01534433': 13, 'n01537544': 14, 'n01558993': 15, 'n01560419': 16
, 'n01580077': 17, 'n01582220': 18, 'n01592084': 19, 'n01601694': 20, 'n01608432': 21, 'n01614925': 22, 'n01616318': 23, 'n01622779': 24
, 'n01629819': 25, 'n01630670': 26, 'n01631663': 27, 'n01632458': 28, 'n01632777': 29, 'n01641577': 30, 'n01644373': 31, 'n01644900': 32
, 'n01664065': 33, 'n01665541': 34, 'n01667114': 35, 'n01667778': 36, 'n01669191': 37, 'n01675722': 38, 'n01677366': 39, 'n01682714': 40
, 'n01685808': 41, 'n01687978': 42, 'n01688243': 43, 'n01689811': 44, 'n01692333': 45, 'n01693334': 46, 'n01694178': 47, 'n01695060': 48
, 'n01697457': 49, 'n01698640': 50, 'n01704323': 51, 'n01728572': 52, 'n01728920': 53, 'n01729322': 54, 'n01729977': 55, 'n01734418': 56
, 'n01735189': 57, 'n01737021': 58, 'n01739381': 59, 'n01740131': 60, 'n01742172': 61, 'n01744401': 62, 'n01748264': 63, 'n01749939': 64
, 'n01751748': 65, 'n01753488': 66, 'n01755581': 67, 'n01756291': 68, 'n01768244': 69, 'n01770081': 70, 'n01770393': 71, 'n01773157': 72
, 'n01773549': 73, 'n01773797': 74, 'n01774384': 75, 'n01774750': 76, 'n01775062': 77, 'n01776313': 78, 'n01784675': 79, 'n01795545': 80
, 'n01796340': 81, 'n01797886': 82, 'n01798484': 83, 'n01806143': 84, 'n01806567': 85, 'n01807496': 86, 'n01817953': 87, 'n01818515': 88
, 'n01819313': 89, 'n01820546': 90, 'n01824575': 91, 'n01828970': 92, 'n01829413': 93, 'n01833805': 94, 'n01843065': 95, 'n01843383': 96
, 'n01847000': 97, 'n01855032': 98, 'n01855672': 99, 'n01860187': 100, 'n01871265': 101, 'n01872401': 102, 'n01873310': 103, 'n01877812': 104
, 'n01882714': 105, 'n01883070': 106, 'n01910747': 107, 'n01914609': 108, 'n01917289': 109, 'n01924916': 110, 'n01930112': 111, 'n01943899': 112
, 'n01944390': 113, 'n01945685': 114, 'n01950731': 115, 'n01955084': 116, 'n01968897': 117, 'n01978287': 118, 'n01978455': 119, 'n01980166': 120
, 'n01981276': 121, 'n01983481': 122, 'n01984695': 123, 'n01985128': 124, 'n01986214': 125, 'n01990800': 126, 'n02002556': 127, 'n02002724': 128
, 'n02006656': 129, 'n02007558': 130, 'n02009229': 131, 'n02009912': 132, 'n02011460': 133, 'n02012849': 134, 'n02013706': 135, 'n02017213': 136
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, 'n09472597': 980, 'n09835506': 981, 'n10148035': 982, 'n10565667': 983, 'n11879895': 984, 'n11939491': 985, 'n12057211': 986, 'n12144580': 987, 'n12267677': 988, 'n12620546': 989, 'n12768682': 990, 'n12985857': 991, 'n12998815': 992, 'n13037406': 993, 'n13040303': 994, 'n13044778': 995
, 'n13052670': 996, 'n13054560': 997, 'n13133613': 998, 'n15075141': 999}
class_names_dict = dict(sorted(class_names_dict.items(), key=lambda x: x[1]))
class_names_2 = list(class_names_dict.keys())
def load_model():
# Load the trained model
model = ImageNetClassifier.load_from_checkpoint(
"logs/checkpoints/epoch=59-val_loss=1.46.ckpt",
map_location="cuda" if torch.cuda.is_available() else "cpu",
#lr=6.28E-02, # This parameter is required but won't be used for inference
num_classes=1000 # Make sure this matches your trained model
)
model.eval()
return model
# Initialize the model
model = load_model()
model.eval()
# Define the preprocessing transforms
transform = transforms.Compose([
transforms.Resize(size=256, antialias=True),
transforms.CenterCrop(224),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
transforms.ToTensor(),
])
def predict_breed(image):
# Convert to PIL Image if needed
if not isinstance(image, Image.Image):
image = Image.fromarray(image)
# Preprocess the image
# Convert to tensor
to_tensor = transforms.ToTensor()
img_tensor = to_tensor(image).unsqueeze(0)
# Make prediction
with torch.no_grad():
outputs = model(img_tensor)
probabilities = torch.nn.functional.softmax(outputs, dim=1)
# Get top 5 predictions
top5_prob, top5_indices = torch.topk(probabilities, 5)
print('top5_prob', top5_prob)
print('top5_indices', top5_indices)
# Create results dictionary
results = {
class_names_2[idx.item()]: prob.item()
for prob, idx in zip(top5_prob[0], top5_indices[0])
}
print(results)
results = {mapping_file_dict[old_key]: results[old_key] for old_key in results.keys()}
print(results)
return results
# Create Gradio interface
iface = gr.Interface(
fn=predict_breed,
inputs=gr.Image(),
outputs=gr.Label(num_top_classes=5),
title="ImageNet-1K ResNet50 Classifier",
description="Upload a image to identify its classification!",
examples=[
# Add paths to example images here
# ["examples/dog1.jpg"],
# ["examples/dog2.jpg"]
# ['data/test/ILSVRC2012_test_00000004.JPEG'],
# ['data/test/ILSVRC2012_test_00000178.JPEG'],
# ["data/test/ILSVRC2012_test_00000188.JPEG"],
# ["data/test/ILSVRC2012_test_00000158.JPEG"],
]
)
# Launch the app
if __name__ == "__main__":
iface.launch()
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