Upload 3 files

app.py

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+import gradio as gr
+import torch
+import torch.nn as nn
+from torchvision import transforms
+from PIL import Image
+import os
+
+# 3. Define the model used for training
+class VeggieNet(nn.Module):
+    def __init__(self, num_classes):
+        super().__init__()
+        self.net = nn.Sequential(
+            nn.Flatten(),
+            nn.Linear(3 * 128 * 128, 512),
+            nn.BatchNorm1d(512),
+            nn.ReLU(),
+            nn.Dropout(0.3),
+            nn.Linear(512, 256),
+            nn.BatchNorm1d(256),
+            nn.ReLU(),
+            nn.Dropout(0.3),
+            nn.Linear(256, 128),
+            nn.BatchNorm1d(128),
+            nn.ReLU(),
+            nn.Dropout(0.3),
+            nn.Linear(128, num_classes)
+        )
+
+    def forward(self, x):
+        return self.net(x)
+
+# Manually loading the class names to match the dataset
+class_names = ['Bean', 'Bitter_Gourd', 'Bottle_Gourd', 'Brinjal', 'Broccoli', 'Cabbage', 'Capsicum', 'Carrot', 'Cauliflower', 'Cucumber', 'Papaya', 'Potato', 'Pumpkin', 'Radish', 'Tomato']
+
+#loading the model
+device = "gpu" if torch.cuda.is_available() else "cpu"
+model = VeggieNet(num_classes=len(class_names))
+model.load_state_dict(torch.load("veggie_net.pth", map_location=device))
+model.eval()
+
+#image preprocessing
+transform = transforms.Compose([
+    transforms.Resize((128, 128)),
+    transforms.ToTensor(),
+    transforms.Normalize((0.5,), (0.5,))
+])
+
+# prediction function
+def predict(image):
+    img = image.convert("RGB")
+    img = transform(img)
+    img = img.unsqueeze(0)
+    with torch.no_grad():
+        outputs = model(img)
+        _, predicted = torch.max(outputs, 1)
+        return class_names[predicted.item()]
+
+# gradio ui
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs="label",
+    title="🥕 Vegetable Image Classifier",
+    description="Upload a vegetable image and the model will try to guess what it is!"
+)
+
+#launching the app
+if __name__  == "__main__":
+    interface.launch()

requirements.txt

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+aiofiles==23.2.1
+annotated-types==0.7.0
+anyio==4.8.0
+argon2-cffi==23.1.0
+argon2-cffi-bindings==21.2.0
+arrow==1.3.0
+asttokens==3.0.0
+async-lru==2.0.4
+attrs==25.1.0
+babel==2.17.0
+beautifulsoup4==4.13.3
+bleach==6.2.0
+certifi==2025.1.31
+cffi==1.17.1
+charset-normalizer==3.4.1
+click==8.1.8
+comm==0.2.2
+contourpy==1.3.1
+cycler==0.12.1
+debugpy==1.8.12
+decorator==5.2.1
+defusedxml==0.7.1
+executing==2.2.0
+fastapi==0.115.11
+fastjsonschema==2.21.1
+ffmpy==0.5.0
+filelock==3.17.0
+fonttools==4.56.0
+fqdn==1.5.1
+fsspec==2025.2.0
+gradio==5.20.1
+gradio_client==1.7.2
+groovy==0.1.2
+h11==0.14.0
+httpcore==1.0.7
+httpx==0.28.1
+huggingface-hub==0.29.3
+idna==3.10
+ipykernel==6.29.5
+ipython==9.0.1
+ipython_pygments_lexers==1.1.1
+ipywidgets==8.1.5
+isoduration==20.11.0
+jedi==0.19.2
+Jinja2==3.1.5
+joblib==1.4.2
+json5==0.10.0
+jsonpointer==3.0.0
+jsonschema==4.23.0
+jsonschema-specifications==2024.10.1
+jupyter==1.1.1
+jupyter-console==6.6.3
+jupyter-events==0.12.0
+jupyter-lsp==2.2.5
+jupyter_client==8.6.3
+jupyter_core==5.7.2
+jupyter_server==2.15.0
+jupyter_server_terminals==0.5.3
+jupyterlab==4.3.5
+jupyterlab_pygments==0.3.0
+jupyterlab_server==2.27.3
+jupyterlab_widgets==3.0.13
+kiwisolver==1.4.8
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.10.1
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+mistune==3.1.2
+mpmath==1.3.0
+nbclient==0.10.2
+nbconvert==7.16.6
+nbformat==5.10.4
+nest-asyncio==1.6.0
+networkx==3.4.2
+notebook==7.3.2
+notebook_shim==0.2.4
+numpy==2.2.3
+nvidia-cublas-cu12==12.4.5.8
+nvidia-cuda-cupti-cu12==12.4.127
+nvidia-cuda-nvrtc-cu12==12.4.127
+nvidia-cuda-runtime-cu12==12.4.127
+nvidia-cudnn-cu12==9.1.0.70
+nvidia-cufft-cu12==11.2.1.3
+nvidia-curand-cu12==10.3.5.147
+nvidia-cusolver-cu12==11.6.1.9
+nvidia-cusparse-cu12==12.3.1.170
+nvidia-cusparselt-cu12==0.6.2
+nvidia-nccl-cu12==2.21.5
+nvidia-nvjitlink-cu12==12.4.127
+nvidia-nvtx-cu12==12.4.127
+orjson==3.10.15
+overrides==7.7.0
+packaging==24.2
+pandas==2.2.3
+pandocfilters==1.5.1
+parso==0.8.4
+pexpect==4.9.0
+pillow==11.1.0
+platformdirs==4.3.6
+prometheus_client==0.21.1
+prompt_toolkit==3.0.50
+psutil==7.0.0
+ptyprocess==0.7.0
+pure_eval==0.2.3
+pycparser==2.22
+pydantic==2.10.6
+pydantic_core==2.27.2
+pydub==0.25.1
+Pygments==2.19.1
+pyparsing==3.2.1
+python-dateutil==2.9.0.post0
+python-json-logger==3.2.1
+python-multipart==0.0.20
+pytz==2025.1
+PyYAML==6.0.2
+pyzmq==26.2.1
+referencing==0.36.2
+requests==2.32.3
+rfc3339-validator==0.1.4
+rfc3986-validator==0.1.1
+rich==13.9.4
+rpds-py==0.23.1
+ruff==0.9.10
+safehttpx==0.1.6
+scikit-learn==1.6.1
+scipy==1.15.2
+semantic-version==2.10.0
+Send2Trash==1.8.3
+setuptools==75.8.2
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.6
+stack-data==0.6.3
+starlette==0.46.1
+sympy==1.13.1
+terminado==0.18.1
+threadpoolctl==3.5.0
+tinycss2==1.4.0
+tomlkit==0.13.2
+torch==2.6.0
+torchvision==0.21.0
+tornado==6.4.2
+tqdm==4.67.1
+traitlets==5.14.3
+triton==3.2.0
+typer==0.15.2
+types-python-dateutil==2.9.0.20241206
+typing_extensions==4.12.2
+tzdata==2025.1
+uri-template==1.3.0
+urllib3==2.3.0
+uvicorn==0.34.0
+wcwidth==0.2.13
+webcolors==24.11.1
+webencodings==0.5.1
+websocket-client==1.8.0
+websockets==15.0.1
+widgetsnbextension==4.0.13

veggie_net.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:84d06bfeaefe102198eb22344af28cc01fbdce2453657ba2b08fdc80c0758d62
+size 101351650