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from pathlib import Path
import torch
import gradio as gr
from torch import nn
LABELS = Path("class_names.txt").read_text().splitlines()
model = nn.Sequential(
nn.Conv2d(1, 32, 3, padding="same"),
nn.ReLU(),
nn.MaxPool2d(2),
nn.Conv2d(32, 64, 3, padding="same"),
nn.ReLU(),
nn.MaxPool2d(2),
nn.Conv2d(64, 128, 3, padding="same"),
nn.ReLU(),
nn.MaxPool2d(2),
nn.Flatten(),
nn.Linear(1152, 256),
nn.ReLU(),
nn.Linear(256, len(LABELS)),
)
state_dict = torch.load("pytorch_model.bin", map_location="cpu")
model.load_state_dict(state_dict, strict=False)
model.eval()
def predict(im):
if isinstance(im, dict): # For sketchpad input
im = im['composite']
# Convert to grayscale and resize to 28x28
import cv2
im_gray = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)
im_resized = cv2.resize(im_gray, (28, 28))
# Convert to tensor and normalize
x = torch.tensor(im_resized, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.0
with torch.no_grad():
out = model(x)
probabilities = torch.nn.functional.softmax(out[0], dim=0)
values, indices = torch.topk(probabilities, 5)
return {LABELS[i]: v.item() for i, v in zip(indices, values)}
interface = gr.Interface(
predict,
inputs="sketchpad",
outputs="label",
theme="huggingface",
title="Sketch Recognition",
description="Who wants to play Pictionary? Draw a common object like a shovel or a laptop, and the algorithm will guess in real time!",
article="<p style='text-align: center'>Sketch Recognition | Demo Model</p>",
live=True,
)
interface.launch(share=True) |