eybro commited on
Commit
815d67b
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1 Parent(s): 1f30c37

Update app.py

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Files changed (1) hide show
  1. app.py +14 -18
app.py CHANGED
@@ -1,5 +1,8 @@
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  import gradio as gr
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  import numpy as np
 
 
 
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  encoded_images = np.load("X_encoded_compressed.npy")
@@ -31,8 +34,14 @@ def get_image(index):
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  return dataset["test"][index-split]
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  def process_image(image):
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- pass
 
 
 
 
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  def inference(image):
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  input_image = process_image(image)
@@ -50,24 +59,11 @@ def inference(image):
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  for i in top4:
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  im = get_image(i)
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  print(im["label"], im["timestamp"])
 
 
 
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- n=2
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- plt.figure(figsize=(8, 8))
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- for i, (image1, image2) in enumerate(zip(top4[:2], top4[2:])):
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- ax = plt.subplot(2, n, i + 1)
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- image1 = get_image(image1)["image"]
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- image2 = get_image(image2)["image"]
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-
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- plt.imshow(image1)
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- plt.gray()
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- ax.get_xaxis().set_visible(False)
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- ax.get_yaxis().set_visible(False)
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-
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- ax = plt.subplot(2, n, i + 1 + n)
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- plt.imshow(image2)
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- plt.gray()
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- ax.get_xaxis().set_visible(False)
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- ax.get_yaxis().set_visible(False)
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  import gradio as gr
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  import numpy as np
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+ from sklearn.metrics.pairwise import euclidean_distances
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+ import cv2
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+
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  encoded_images = np.load("X_encoded_compressed.npy")
 
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  return dataset["test"][index-split]
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  def process_image(image):
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+ img = np.array(image)
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+ img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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+ img = cv2.resize(img, (64, 64))
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+ img = img.astype('float32')
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+ img /= 255.0
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+ return img
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+
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  def inference(image):
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  input_image = process_image(image)
 
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  for i in top4:
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  im = get_image(i)
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  print(im["label"], im["timestamp"])
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+
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+ result_image = get_image(top4[0])
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+ result = result_image['label'] + result_image['timestamp']
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+ return result
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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