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Sleeping
Oliver Hamilton
commited on
Commit
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50a6ee6
1
Parent(s):
d7953e2
Update app.py
Browse files
app.py
CHANGED
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@@ -12,10 +12,6 @@ deployment = Deployment.from_folder("deployment")
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deployment.load_inference_models(device="CPU")
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def is_valid_url(url):
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pattern = r'^(https?|ftp)://[^\s/$.?#].[^\s]*$'
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return re.match(pattern, url) is not None
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def resize_image(image, target_dimension):
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height, width = image.shape[:2]
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@@ -27,41 +23,22 @@ def resize_image(image, target_dimension):
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return resized_image
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def infer(image=None
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if image is None and url is None:
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return [None,'Error: No image or URL provided']
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if image is None:
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if not is_valid_url(url):
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return [None,'Error: URL appears to be invalid']
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req = urlopen(url)
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arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
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image = cv2.imdecode(arr, -1)
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if image is None:
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return [None, f'Error: Unable to fetch image from {url}']
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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image = resize_image(image, 1200)
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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prediction = deployment.infer(image)
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output = show_image_with_annotation_scene(
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output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
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return [output, prediction.overview]
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interface = gr.Interface(fn=infer,
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inputs=['image'
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outputs=['image', 'text'],
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allow_flagging='manual',
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flagging_dir='flagged',
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examples=[
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["bird_example.jpg",""],
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[None,"https://upload.wikimedia.org/wikipedia/commons/9/9a/Pinz%C3%B3n_azul_de_Gran_Canaria_%28macho%29%2C_M._A._Pe%C3%B1a.jpg"],
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[None, "https://upload.wikimedia.org/wikipedia/commons/2/2f/Phaethon_lepturus_%28Warwick%2C_Bermuda%29_%28cropped%29.jpg"]
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])
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interface.launch()
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deployment.load_inference_models(device="CPU")
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def resize_image(image, target_dimension):
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height, width = image.shape[:2]
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return resized_image
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def infer(image=None):
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if image is None:
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return [None,'Error: No image provided']
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image = resize_image(image, 1200)
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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prediction = deployment.infer(image)
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output = show_image_with_annotation_scene(image, prediction, show_results=False)
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return [output, prediction.overview]
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interface = gr.Interface(fn=infer,
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inputs=['image'],
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outputs=['image', 'text'],
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allow_flagging='manual',
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flagging_dir='flagged',
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examples=["no_bird.jpg", "bird_example.jpg"])
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interface.launch()
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