Add local image classifier model

.ipynb_checkpoints/app-checkpoint.py

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+import gradio as gr
+import spaces
+import torch
+
+zero = torch.Tensor([0]).cuda()
+print(zero.device) # <-- 'cpu' 🤔
+
+@spaces.GPU
+def greet(n):
+    print(zero.device) # <-- 'cuda:0' 🤗
+    return f"Hello {zero + n} Tensor"
+
+demo = gr.Interface(fn=greet, inputs=gr.Number(), outputs=gr.Text())
+demo.launch()

app.py

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+import gradio as gr
+from transformers import pipeline
+
+
+classifier = pipeline(
+    task="image-classification",
+    model="model",
+    image_processor="model",
+)
+
+
+def predict(image):
+    results = classifier(image, top_k=3)
+    return {item["label"]: item["score"] for item in results}
+
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Upload image"),
+    outputs=gr.Label(num_top_classes=3, label="Prediction"),
+    title="Ball Sport Classifier",
+)
+
+
+if __name__ == "__main__":
+    demo.launch()

model/config.json

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+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "badminton",
+    "1": "pickleball",
+    "2": "tennis"
+  },
+  "label2id": {
+    "badminton": 0,
+    "pickleball": 1,
+    "tennis": 2
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "problem_type": "single_label_classification",
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "5.13.0",
+  "use_cache": false
+}

model/model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1291f97f4bcc6a53ca253b102c61442290a56432e66b48ba7ff7d27f56422567
+size 94311148

model/preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

model/training_args.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7440d81eff1081b6992c725d3d12fb81c83e834772e0b32b775e2a4745c22af2
+size 5137

requirements.txt

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+gradio
+torch
+transformers
+safetensors