Upload 4 files

app.py

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+import gradio as gr
+import onnxruntime as ort
+import numpy as np
+import torch
+from PIL import Image
+import torchvision.transforms as T
+import cv2
+
+# Load labels
+with open("labels.txt") as f:
+    LABELS = [l.strip() for l in f.readlines()]
+
+# Load ONNX model
+session = ort.InferenceSession("model.onnx")
+
+# Image preprocessing
+transform = T.Compose([
+    T.Resize((224, 224)),
+    T.ToTensor(),
+])
+
+def predict(image):
+    if image is None:
+        return "No image provided", {}
+
+    # Convert OpenCV webcam frame to PIL
+    if isinstance(image, np.ndarray):
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        image = Image.fromarray(image)
+
+    img = transform(image).unsqueeze(0).numpy()
+
+    outputs = session.run(None, {"images": img})[0]
+    probs = torch.softmax(torch.tensor(outputs), dim=1)[0]
+
+    result = {LABELS[i]: float(probs[i]) for i in range(len(LABELS))}
+    top_idx = torch.argmax(probs).item()
+
+    return LABELS[top_idx], result
+
+# Gradio UI
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(source="webcam", type="numpy", label="Capture or Upload Face"),
+    outputs=[
+        gr.Label(label="Predicted Emotion"),
+        gr.JSON(label="Confidence Scores")
+    ],
+    title="Face Emotion Recognition",
+    description="Capture a live face or upload an image to classify emotions."
+)
+
+interface.launch()

labels.txt

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+Angry
+Fear
+Happy
+Sad
+Suprise

model.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cb9dedccf5797b19b30ad9e3efe9a6cb4aff311f80d298cb946c6cb3c64e5774
+size 6176368

requirements.txt

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+absl-py==2.3.1
+asttokens==3.0.0
+astunparse==1.6.3
+certifi==2025.11.12
+charset-normalizer==3.4.4
+coloredlogs==15.0.1
+comm==0.2.2
+contourpy==1.3.3
+cycler==0.12.1
+debugpy==1.8.14
+decorator==5.2.1
+executing==2.2.0
+filelock==3.20.0
+flatbuffers==25.2.10
+fonttools==4.61.0
+fsspec==2025.10.0
+gast==0.6.0
+google-pasta==0.2.0
+grpcio==1.73.1
+h5py==3.14.0
+humanfriendly==10.0
+idna==3.11
+ipykernel==6.29.5
+ipython==9.4.0
+ipython-pygments-lexers==1.1.1
+jedi==0.19.2
+jinja2==3.1.6
+jupyter-client==8.6.3
+jupyter-core==5.8.1
+keras==3.10.0
+kiwisolver==1.4.9
+libclang==18.1.1
+markdown==3.8.2
+markdown-it-py==3.0.0
+markupsafe==3.0.3
+matplotlib==3.10.7
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+ml-dtypes==0.5.1
+mpmath==1.3.0
+namex==0.1.0
+nest-asyncio==1.6.0
+networkx==3.6
+numpy==2.3.5
+nvidia-cublas-cu12==12.8.4.1
+nvidia-cuda-cupti-cu12==12.8.90
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cudnn-cu12==9.10.2.21
+nvidia-cufft-cu12==11.3.3.83
+nvidia-cufile-cu12==1.13.1.3
+nvidia-curand-cu12==10.3.9.90
+nvidia-cusolver-cu12==11.7.3.90
+nvidia-cusparse-cu12==12.5.8.93
+nvidia-cusparselt-cu12==0.7.1
+nvidia-nccl-cu12==2.27.5
+nvidia-nvjitlink-cu12==12.8.93
+nvidia-nvshmem-cu12==3.3.20
+nvidia-nvtx-cu12==12.8.90
+onnxruntime==1.23.2
+opencv-python==4.11.0.86
+opt-einsum==3.4.0
+optree==0.16.0
+packaging==25.0
+pandas==2.3.1
+parso==0.8.4
+pexpect==4.9.0
+pillow==12.0.0
+platformdirs==4.3.8
+polars==1.35.2
+polars-runtime-32==1.35.2
+prompt-toolkit==3.0.51
+protobuf==5.29.5
+psutil==7.1.3
+ptyprocess==0.7.0
+pure-eval==0.2.3
+pygments==2.19.2
+pyparsing==3.2.5
+python-dateutil==2.9.0.post0
+pytz==2025.2
+pyyaml==6.0.3
+pyzmq==27.0.0
+requests==2.32.5
+rich==14.0.0
+scipy==1.16.3
+setuptools==80.9.0
+six==1.17.0
+stack-data==0.6.3
+sympy==1.14.0
+tensorboard==2.19.0
+tensorboard-data-server==0.7.2
+tensorflow==2.19.0
+termcolor==3.1.0
+torch==2.9.1
+torchvision==0.24.1
+tornado==6.5.1
+traitlets==5.14.3
+triton==3.5.1
+typing-extensions==4.15.0
+tzdata==2025.2
+ultralytics==8.3.234
+ultralytics-thop==2.0.18
+urllib3==2.5.0
+wcwidth==0.2.13
+werkzeug==3.1.3
+wheel==0.45.1
+wrapt==1.17.2