show classs names

app.py

@@ -7,12 +7,39 @@ import numpy as np
 import matplotlib.pyplot as plt
 from io import BytesIO
 from PIL import Image
-
+import csv
 from transformers import AutoFeatureExtractor, AutoModelForVideoClassification
 
 # Specify the model checkpoint for TimeSformer.
 MODEL_NAME = "facebook/timesformer-base-finetuned-k400"
 
+def load_kinetics_labels(csv_path="kinetics-400-class-names.csv"):
+    """
+    Loads the Kinetics-400 labels from a CSV file.
+    Expected CSV format:
+        id,name
+        0,abseiling
+        1,air drumming
+        ...
+        399,zumba
+    Returns a dictionary mapping string IDs to label names.
+    """
+    labels = {}
+    try:
+        with open(csv_path, "r", encoding="utf-8") as f:
+            reader = csv.reader(f)
+            # Skip header if present
+            header = next(reader)
+            if "id" not in header[0].lower():
+                f.seek(0)
+                reader = csv.reader(f)
+            for row in reader:
+                if len(row) >= 2:
+                    labels[row[0].strip()] = row[1].strip()
+    except Exception as e:
+        print("Error reading CSV mapping:", e)
+    return labels
+
 def extract_frames(video_path, num_frames=16, target_size=(224, 224)):
     """
     Extract up to `num_frames` uniformly-sampled frames from the video.
@@ -43,14 +70,23 @@ def classify_video(video_path):
     """
     Loads the TimeSformer model and feature extractor inside the GPU context,
     extracts frames from the video, runs inference, and returns:
-      1. A text string of the top 5 predicted action labels with their class IDs and probabilities.
-      2. A bar chart image showing the distribution over the top predictions.
+      1. A text string of the top 5 predicted actions (with class ID and descriptive label)
+         along with their probabilities.
+      2. A bar chart (as a PIL Image) showing the prediction distribution.
     """
-    # Load the feature extractor and model inside the GPU context.
+    # Load the feature extractor and model.
     feature_extractor = AutoFeatureExtractor.from_pretrained(MODEL_NAME)
     model = AutoModelForVideoClassification.from_pretrained(MODEL_NAME)
     model.eval()
     
+    # Load the complete Kinetics-400 mapping from CSV.
+    kinetics_id2label = load_kinetics_labels("kinetics-400-class-names.csv")
+    if kinetics_id2label:
+        print("Loaded complete Kinetics-400 mapping from CSV.")
+    else:
+        print("Warning: Could not load Kinetics-400 mapping; using default labels.")
+    model.config.id2label = kinetics_id2label if kinetics_id2label else model.config.id2label
+
     # Determine the device.
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     model.to(device)
@@ -77,14 +113,11 @@ def classify_video(video_path):
     top_probs = top_probs.cpu().numpy()
     top_indices = top_indices.cpu().numpy()
     
-    # Retrieve the label mapping from model config.
-    id2label = model.config.id2label if hasattr(model.config, "id2label") else {}
-    
-    # Prepare textual results showing both ID and label.
+    # Prepare textual results including both ID and label.
     results = []
     x_labels = []
     for idx, prob in zip(top_indices, top_probs):
-        label = id2label.get(str(idx), f"Class {idx}")
+        label = kinetics_id2label.get(str(idx), f"Class {idx}")
         results.append(f"ID {idx} - {label}: {prob:.3f}")
         x_labels.append(f"ID {idx}\n{label}")
     results_text = "\n".join(results)
@@ -124,8 +157,8 @@ demo = gr.Interface(
     title="Video Human Detection Demo using TimeSformer",
     description=(
         "Upload a video clip to see the top predicted human action labels using the TimeSformer model "
-        "(fine-tuned on Kinetics-400). The output shows each prediction (with class ID and label) and a bar chart "
-        "of the distribution over the top 5 predictions."
+        "(fine-tuned on Kinetics-400). The output displays each prediction's class ID and label, along with "
+        "a bar chart distribution of the top 5 predictions. A complete Kinetics-400 mapping is loaded from a CSV file."
     )
 )
 

kinetics-400-class-names.csv

@@ -0,0 +1,401 @@
+id,name
+0,abseiling
+1,air drumming
+2,answering questions
+3,applauding
+4,applying cream
+5,archery
+6,arm wrestling
+7,arranging flowers
+8,assembling computer
+9,auctioning
+10,baby waking up
+11,baking cookies
+12,balloon blowing
+13,bandaging
+14,barbequing
+15,bartending
+16,beatboxing
+17,bee keeping
+18,belly dancing
+19,bench pressing
+20,bending back
+21,bending metal
+22,biking through snow
+23,blasting sand
+24,blowing glass
+25,blowing leaves
+26,blowing nose
+27,blowing out candles
+28,bobsledding
+29,bookbinding
+30,bouncing on trampoline
+31,bowling
+32,braiding hair
+33,breading or breadcrumbing
+34,breakdancing
+35,brush painting
+36,brushing hair
+37,brushing teeth
+38,building cabinet
+39,building shed
+40,bungee jumping
+41,busking
+42,canoeing or kayaking
+43,capoeira
+44,carrying baby
+45,cartwheeling
+46,carving pumpkin
+47,catching fish
+48,catching or throwing baseball
+49,catching or throwing frisbee
+50,catching or throwing softball
+51,celebrating
+52,changing oil
+53,changing wheel
+54,checking tires
+55,cheerleading
+56,chopping wood
+57,clapping
+58,clay pottery making
+59,clean and jerk
+60,cleaning floor
+61,cleaning gutters
+62,cleaning pool
+63,cleaning shoes
+64,cleaning toilet
+65,cleaning windows
+66,climbing a rope
+67,climbing ladder
+68,climbing tree
+69,contact juggling
+70,cooking chicken
+71,cooking egg
+72,cooking on campfire
+73,cooking sausages
+74,counting money
+75,country line dancing
+76,cracking neck
+77,crawling baby
+78,crossing river
+79,crying
+80,curling hair
+81,cutting nails
+82,cutting pineapple
+83,cutting watermelon
+84,dancing ballet
+85,dancing charleston
+86,dancing gangnam style
+87,dancing macarena
+88,deadlifting
+89,decorating the christmas tree
+90,digging
+91,dining
+92,disc golfing
+93,diving cliff
+94,dodgeball
+95,doing aerobics
+96,doing laundry
+97,doing nails
+98,drawing
+99,dribbling basketball
+100,drinking
+101,drinking beer
+102,drinking shots
+103,driving car
+104,driving tractor
+105,drop kicking
+106,drumming fingers
+107,dunking basketball
+108,dying hair
+109,eating burger
+110,eating cake
+111,eating carrots
+112,eating chips
+113,eating doughnuts
+114,eating hotdog
+115,eating ice cream
+116,eating spaghetti
+117,eating watermelon
+118,egg hunting
+119,exercising arm
+120,exercising with an exercise ball
+121,extinguishing fire
+122,faceplanting
+123,feeding birds
+124,feeding fish
+125,feeding goats
+126,filling eyebrows
+127,finger snapping
+128,fixing hair
+129,flipping pancake
+130,flying kite
+131,folding clothes
+132,folding napkins
+133,folding paper
+134,front raises
+135,frying vegetables
+136,garbage collecting
+137,gargling
+138,getting a haircut
+139,getting a tattoo
+140,giving or receiving award
+141,golf chipping
+142,golf driving
+143,golf putting
+144,grinding meat
+145,grooming dog
+146,grooming horse
+147,gymnastics tumbling
+148,hammer throw
+149,headbanging
+150,headbutting
+151,high jump
+152,high kick
+153,hitting baseball
+154,hockey stop
+155,holding snake
+156,hopscotch
+157,hoverboarding
+158,hugging
+159,hula hooping
+160,hurdling
+161,hurling (sport)
+162,ice climbing
+163,ice fishing
+164,ice skating
+165,ironing
+166,javelin throw
+167,jetskiing
+168,jogging
+169,juggling balls
+170,juggling fire
+171,juggling soccer ball
+172,jumping into pool
+173,jumpstyle dancing
+174,kicking field goal
+175,kicking soccer ball
+176,kissing
+177,kitesurfing
+178,knitting
+179,krumping
+180,laughing
+181,laying bricks
+182,long jump
+183,lunge
+184,making a cake
+185,making a sandwich
+186,making bed
+187,making jewelry
+188,making pizza
+189,making snowman
+190,making sushi
+191,making tea
+192,marching
+193,massaging back
+194,massaging feet
+195,massaging legs
+196,massaging person's head
+197,milking cow
+198,mopping floor
+199,motorcycling
+200,moving furniture
+201,mowing lawn
+202,news anchoring
+203,opening bottle
+204,opening present
+205,paragliding
+206,parasailing
+207,parkour
+208,passing American football (in game)
+209,passing American football (not in game)
+210,peeling apples
+211,peeling potatoes
+212,petting animal (not cat)
+213,petting cat
+214,picking fruit
+215,planting trees
+216,plastering
+217,playing accordion
+218,playing badminton
+219,playing bagpipes
+220,playing basketball
+221,playing bass guitar
+222,playing cards
+223,playing cello
+224,playing chess
+225,playing clarinet
+226,playing controller
+227,playing cricket
+228,playing cymbals
+229,playing didgeridoo
+230,playing drums
+231,playing flute
+232,playing guitar
+233,playing harmonica
+234,playing harp
+235,playing ice hockey
+236,playing keyboard
+237,playing kickball
+238,playing monopoly
+239,playing organ
+240,playing paintball
+241,playing piano
+242,playing poker
+243,playing recorder
+244,playing saxophone
+245,playing squash or racquetball
+246,playing tennis
+247,playing trombone
+248,playing trumpet
+249,playing ukulele
+250,playing violin
+251,playing volleyball
+252,playing xylophone
+253,pole vault
+254,presenting weather forecast
+255,pull ups
+256,pumping fist
+257,pumping gas
+258,punching bag
+259,punching person (boxing)
+260,push up
+261,pushing car
+262,pushing cart
+263,pushing wheelchair
+264,reading book
+265,reading newspaper
+266,recording music
+267,riding a bike
+268,riding camel
+269,riding elephant
+270,riding mechanical bull
+271,riding mountain bike
+272,riding mule
+273,riding or walking with horse
+274,riding scooter
+275,riding unicycle
+276,ripping paper
+277,robot dancing
+278,rock climbing
+279,rock scissors paper
+280,roller skating
+281,running on treadmill
+282,sailing
+283,salsa dancing
+284,sanding floor
+285,scrambling eggs
+286,scuba diving
+287,setting table
+288,shaking hands
+289,shaking head
+290,sharpening knives
+291,sharpening pencil
+292,shaving head
+293,shaving legs
+294,shearing sheep
+295,shining shoes
+296,shooting basketball
+297,shooting goal (soccer)
+298,shot put
+299,shoveling snow
+300,shredding paper
+301,shuffling cards
+302,side kick
+303,sign language interpreting
+304,singing
+305,situp
+306,skateboarding
+307,ski jumping
+308,skiing (not slalom or crosscountry)
+309,skiing crosscountry
+310,skiing slalom
+311,skipping rope
+312,skydiving
+313,slacklining
+314,slapping
+315,sled dog racing
+316,smoking
+317,smoking hookah
+318,snatch weight lifting
+319,sneezing
+320,sniffing
+321,snorkeling
+322,snowboarding
+323,snowkiting
+324,snowmobiling
+325,somersaulting
+326,spinning poi
+327,spray painting
+328,spraying
+329,springboard diving
+330,squat
+331,sticking tongue out
+332,stomping grapes
+333,stretching arm
+334,stretching leg
+335,strumming guitar
+336,surfing crowd
+337,surfing water
+338,sweeping floor
+339,swimming backstroke
+340,swimming breast stroke
+341,swimming butterfly stroke
+342,swing dancing
+343,swinging legs
+344,swinging on something
+345,sword fighting
+346,tai chi
+347,taking a shower
+348,tango dancing
+349,tap dancing
+350,tapping guitar
+351,tapping pen
+352,tasting beer
+353,tasting food
+354,testifying
+355,texting
+356,throwing axe
+357,throwing ball
+358,throwing discus
+359,tickling
+360,tobogganing
+361,tossing coin
+362,tossing salad
+363,training dog
+364,trapezing
+365,trimming or shaving beard
+366,trimming trees
+367,triple jump
+368,tying bow tie
+369,tying knot (not on a tie)
+370,tying tie
+371,unboxing
+372,unloading truck
+373,using computer
+374,using remote controller (not gaming)
+375,using segway
+376,vault
+377,waiting in line
+378,walking the dog
+379,washing dishes
+380,washing feet
+381,washing hair
+382,washing hands
+383,water skiing
+384,water sliding
+385,watering plants
+386,waxing back
+387,waxing chest
+388,waxing eyebrows
+389,waxing legs
+390,weaving basket
+391,welding
+392,whistling
+393,windsurfing
+394,wrapping present
+395,wrestling
+396,writing
+397,yawning
+398,yoga
+399,zumba