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Running
test out nsfw
Browse files- app.py +18 -2
- requirements.txt +2 -1
app.py
CHANGED
@@ -4,8 +4,11 @@ import gradio as gr
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from fastcore.all import *
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from fastai.vision.all import *
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import numpy as np
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import timm
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def parent_labels(o):
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"Label `item` with the parent folder name."
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@@ -31,10 +34,23 @@ def predict(image, vtt):
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sprite = PILImage.create(image)
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offsets = []
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images = []
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for left, top, right, bottom in getVTToffsets(vtt):
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offsets.append((left, top, right, bottom))
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cut_frame = sprite.crop((left, top, left + right, top + bottom))
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# create dataset
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test_dl = learn.dls.test_dl(images, bs=64)
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from fastcore.all import *
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from fastai.vision.all import *
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import numpy as np
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import opennsfw2 as n2
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import timm
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model = n2.make_open_nsfw_model()
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def parent_labels(o):
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"Label `item` with the parent folder name."
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sprite = PILImage.create(image)
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offsets = []
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images = []
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tensors = []
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pre_process_data = []
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for left, top, right, bottom in getVTToffsets(vtt):
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cut_frame = sprite.crop((left, top, left + right, top + bottom))
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image = n2.preprocess_image(cut_frame, n2.Preprocessing.YAHOO)
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pre_process_data.append((np.expand_dims(image, axis=0), cut_frame, (left, top, right, bottom)))
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offsets = []
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images = []
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tensors = [i[0] for i in pre_process_data]
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predictions = model.predict(np.vstack(tensors))
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for i, prediction in enumerate(predictions):
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if prediction[0] < 0.5:
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images.append(PILImage.create(np.asarray(pre_process_data[i][1])))
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offsets.append(pre_process_data[i][2])
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# create dataset
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test_dl = learn.dls.test_dl(images, bs=64)
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requirements.txt
CHANGED
@@ -1,4 +1,5 @@
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fastai==2.7.7
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numpy==1.
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timm==0.6.7
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gradio
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fastai==2.7.7
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numpy==1.24.2
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timm==0.6.7
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opennsfw2==0.10.2
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gradio
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