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  1. README.md +5 -6
  2. app.py +52 -0
  3. bike.jpg +0 -0
  4. car.jpg +0 -0
  5. food.jpg +0 -0
  6. requirements.txt +3 -0
README.md CHANGED
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  ---
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- title: Opensource ImageClassifer Combo
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- emoji: πŸ’»
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- colorFrom: gray
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- colorTo: pink
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  sdk: gradio
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- sdk_version: 3.23.0
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  app_file: app.py
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  pinned: false
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- license: openrail
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  ---
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  ---
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+ title: Battle Of The Image Classifiers
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+ emoji: 🐨
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+ colorFrom: green
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+ colorTo: gray
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  sdk: gradio
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+ sdk_version: 3.16.1
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  app_file: app.py
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  pinned: false
 
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  ---
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py ADDED
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+ import gradio as gr
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+ from transformers import pipeline
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+
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+ model_names = [
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+ "apple/mobilevit-small",
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+ "facebook/deit-base-patch16-224",
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+ "facebook/convnext-base-224",
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+ "google/vit-base-patch16-224",
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+ "google/mobilenet_v2_1.4_224",
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+ "microsoft/resnet-50",
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+ "microsoft/swin-base-patch4-window7-224",
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+ "microsoft/beit-base-patch16-224",
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+ "nvidia/mit-b0",
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+ "shi-labs/nat-base-in1k-224",
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+ "shi-labs/dinat-base-in1k-224",
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+ ]
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+
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+
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+ def process(image_file, top_k):
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+ labels = []
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+ for m in model_names:
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+ p = pipeline("image-classification", model=m)
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+ pred = p(image_file)
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+ labels.append({x["label"]: x["score"] for x in pred[:top_k]})
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+ return labels
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+
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+
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+ # Inputs
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+ image = gr.Image(type="filepath", label="Upload an image")
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+ top_k = gr.Slider(minimum=1, maximum=5, step=1, value=5, label="Top k classes")
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+
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+ # Output
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+ labels = [gr.Label(label=m) for m in model_names]
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+
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+ description = "This Space lets you quickly compare the most popular image classifiers available on the hub, including the recent NAT and DINAT models. All of them have been fine-tuned on the ImageNet-1k dataset. Anecdotally, the three sample images have been generated with a Stable Diffusion model :)"
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+
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+ iface = gr.Interface(
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+ theme="huggingface",
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+ description=description,
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+ layout="horizontal",
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+ fn=process,
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+ inputs=[image, top_k],
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+ outputs=labels,
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+ examples=[
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+ ["bike.jpg", 5],
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+ ["car.jpg", 5],
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+ ["food.jpg", 5],
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+ ],
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+ allow_flagging="never",
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+ )
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+
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+ iface.launch()
bike.jpg ADDED
car.jpg ADDED
food.jpg ADDED
requirements.txt ADDED
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+ torch==1.13.1
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+ transformers>=4.25.1
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+ https://shi-labs.com/natten/wheels/cpu/torch1.13/natten-0.14.4%2Btorch1130cpu-cp38-cp38-linux_x86_64.whl