Add initial setup files

.gitignore

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+.DS_Store
+*~

app.py

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+import gradio as gr
+import coremltools as ct
+import numpy as np
+import requests
+import huggingface_hub as hf
+from huggingface_hub import hf_hub_download
+from huggingface_hub import login
+import os
+import PIL
+
+#login()
+
+read_key = os.environ.get('HF_TOKEN', True)
+extractor_path = hf_hub_download(repo_id="crossprism/efficientnetv221k-M", filename="efficientnetV2M21kExtractor.mlmodel", use_auth_token  = read_key)
+classifier_path = hf_hub_download(repo_id="crossprism/tesla_sentry_dings", filename="tesla_sentry_door_ding.mlpackage/Data/com.apple.CoreML/tesla_door_dings.mlmodel", use_auth_token = read_key)
+
+
+print(f"Loading extractor...{extractor_path}")
+extractor = ct.models.MLModel(extractor_path)
+print(f"Loading classifier...{classifier_path}")
+classifier = ct.models.MLModel(classifier_path)
+
+def classify_image(image):
+    image = image.resize((480,480))
+    features = extractor.predict({"image":image})
+    print(features)
+    features = features["Identity"]
+    isDing = classifier.predict({"features":features[0]})
+    print(isDing)
+    isDing = isDing["Identity"]
+    return {'ding': isDing["ding"]}
+
+image = gr.Image(type='pil')
+label = gr.Label(num_top_classes=3)
+
+gr.Interface(fn=classify_image, inputs=image, outputs=label, examples = [["test.jpg"]]).launch()
+

requirements.txt

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+python==3.9
+coremltools=5.1