v2
Browse files- app.py +14 -13
- flagged/img/0ce3b8e7aa4df42ff211fc38c49a73e486b3accf/tmpva0ptb1u.jpg +0 -0
- flagged/img/302233888fff6cbb20dc571a2aa2f4ca4582a82c/tmp10zz4cfv.jpg +0 -0
- flagged/img/c55bbd60f3f87a4a3ae82b289045d0f9471ea3b4/tmp94igg62a.jpg +0 -0
- flagged/img/edf8db2e47ee5fb67942da896db080edef19574e/tmp1qgn1e9n.jpg +0 -0
- flagged/log.csv +5 -0
- flagged/output/tmpdi2ceh8q.json +1 -0
- flagged/output/tmplsiza_8_.json +1 -0
- flagged/output/tmpoz3eynnc.json +1 -0
- flagged/output/tmpy4wj9m6r.json +1 -0
- img/dress.jpg +0 -0
- img/hat.jpg +0 -0
- img/longsleeve.jpg +0 -0
- img/outwear.jpg +0 -0
- img/pants.jpg +0 -0
- img/shirt.jpg +0 -0
- img/shoes.jpg +0 -0
- img/short.jpg +0 -0
- img/shorts.jpg +0 -1
- img/skirt.jpg +0 -0
- img/t-shirt.jpg +0 -0
- requirements.txt +1 -1
app.py
CHANGED
@@ -7,21 +7,21 @@ import numpy as np
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model = from_pretrained_keras("yusyel/clothing")
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class_names=["dress
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"hat
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"longsleee
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"outwear
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"pants
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"shirt
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"shoes
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"shorts
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"skirt
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"t-shirt
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def preprocess_image(img):
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img = load_img(img, target_size=(
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img = image.img_to_array(img)
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img = np.expand_dims(img, axis=0)
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img /= 255.0
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@@ -33,7 +33,8 @@ def preprocess_image(img):
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def predict(img):
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img = preprocess_image(img)
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pred = model.predict(img)
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print(pred)
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return dict(zip(class_names, pred))
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@@ -50,7 +51,7 @@ demo = gr.Interface(
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["./img/pants.jpg"],
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["./img/shirt.jpg"],
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["./img/shoes.jpg"],
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["./img/
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["./img/skirt.jpg"],
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["./img/t-shirt.jpg"],
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],
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model = from_pretrained_keras("yusyel/clothing")
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class_names=["dress",
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"hat",
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"longsleee",
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"outwear",
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"pants",
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"shirt",
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"shoes",
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"shorts",
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"skirt",
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"t-shirt"]
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def preprocess_image(img):
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img = load_img(img, target_size=(299, 299, 3))
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img = image.img_to_array(img)
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img = np.expand_dims(img, axis=0)
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img /= 255.0
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def predict(img):
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img = preprocess_image(img)
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pred = model.predict(img)
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print(pred)
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pred = np.round(np.squeeze(pred).astype(float),5)
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print(pred)
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return dict(zip(class_names, pred))
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["./img/pants.jpg"],
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["./img/shirt.jpg"],
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["./img/shoes.jpg"],
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["./img/short.jpg"],
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["./img/skirt.jpg"],
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["./img/t-shirt.jpg"],
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],
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flagged/img/0ce3b8e7aa4df42ff211fc38c49a73e486b3accf/tmpva0ptb1u.jpg
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flagged/img/302233888fff6cbb20dc571a2aa2f4ca4582a82c/tmp10zz4cfv.jpg
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flagged/img/c55bbd60f3f87a4a3ae82b289045d0f9471ea3b4/tmp94igg62a.jpg
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flagged/img/edf8db2e47ee5fb67942da896db080edef19574e/tmp1qgn1e9n.jpg
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flagged/log.csv
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img,output,flag,username,timestamp
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/home/yusuf/okul/clothing/flagged/img/edf8db2e47ee5fb67942da896db080edef19574e/tmp1qgn1e9n.jpg,/home/yusuf/okul/clothing/flagged/output/tmpoz3eynnc.json,,,2023-08-22 19:05:19.413148
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/home/yusuf/okul/clothing/flagged/img/302233888fff6cbb20dc571a2aa2f4ca4582a82c/tmp10zz4cfv.jpg,/home/yusuf/okul/clothing/flagged/output/tmpy4wj9m6r.json,,,2023-08-22 19:46:06.542922
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/home/yusuf/okul/clothing/flagged/img/0ce3b8e7aa4df42ff211fc38c49a73e486b3accf/tmpva0ptb1u.jpg,/home/yusuf/okul/clothing/flagged/output/tmpdi2ceh8q.json,,,2023-08-22 19:46:07.960612
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/home/yusuf/okul/clothing/flagged/img/c55bbd60f3f87a4a3ae82b289045d0f9471ea3b4/tmp94igg62a.jpg,/home/yusuf/okul/clothing/flagged/output/tmplsiza_8_.json,,,2023-08-22 19:46:13.040043
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flagged/output/tmpdi2ceh8q.json
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{"label": "t-shirt", "confidences": [{"label": "t-shirt", "confidence": 6.181421756744385}, {"label": "longsleee", "confidence": 3.4848127365112305}, {"label": "dress", "confidence": 2.3854408264160156}, {"label": "shirt", "confidence": -1.1809395551681519}, {"label": "shorts", "confidence": -2.108891248703003}, {"label": "shoes", "confidence": -3.061194658279419}, {"label": "hat", "confidence": -3.9095823764801025}, {"label": "outwear", "confidence": -4.6832733154296875}, {"label": "pants", "confidence": -5.055410861968994}, {"label": "skirt", "confidence": -5.316753387451172}]}
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flagged/output/tmplsiza_8_.json
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{"label": "t-shirt", "confidences": [{"label": "t-shirt", "confidence": 6.181421756744385}, {"label": "longsleee", "confidence": 3.4848127365112305}, {"label": "dress", "confidence": 2.3854408264160156}, {"label": "shirt", "confidence": -1.1809395551681519}, {"label": "shorts", "confidence": -2.108891248703003}, {"label": "shoes", "confidence": -3.061194658279419}, {"label": "hat", "confidence": -3.9095823764801025}, {"label": "outwear", "confidence": -4.6832733154296875}, {"label": "pants", "confidence": -5.055410861968994}, {"label": "skirt", "confidence": -5.316753387451172}]}
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flagged/output/tmpoz3eynnc.json
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{"label": "t-shirt", "confidences": [{"label": "t-shirt", "confidence": 6.181421756744385}, {"label": "longsleee", "confidence": 3.4848124980926514}, {"label": "dress", "confidence": 2.385441303253174}, {"label": "shirt", "confidence": -1.1809393167495728}, {"label": "shorts", "confidence": -2.108891487121582}, {"label": "shoes", "confidence": -3.0611960887908936}, {"label": "hat", "confidence": -3.9095826148986816}, {"label": "outwear", "confidence": -4.683272838592529}, {"label": "pants", "confidence": -5.055410385131836}, {"label": "skirt", "confidence": -5.316753387451172}]}
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flagged/output/tmpy4wj9m6r.json
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{"label": "t-shirt", "confidences": [{"label": "t-shirt", "confidence": 6.181421756744385}, {"label": "longsleee", "confidence": 3.4848127365112305}, {"label": "dress", "confidence": 2.3854408264160156}, {"label": "shirt", "confidence": -1.1809395551681519}, {"label": "shorts", "confidence": -2.108891248703003}, {"label": "shoes", "confidence": -3.061194658279419}, {"label": "hat", "confidence": -3.9095823764801025}, {"label": "outwear", "confidence": -4.6832733154296875}, {"label": "pants", "confidence": -5.055410861968994}, {"label": "skirt", "confidence": -5.316753387451172}]}
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img/dress.jpg
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img/hat.jpg
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img/longsleeve.jpg
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img/outwear.jpg
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img/pants.jpg
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img/shirt.jpg
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img/shoes.jpg
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img/short.jpg
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img/shorts.jpg
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img/skirt.jpg
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img/t-shirt.jpg
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requirements.txt
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@@ -1,3 +1,3 @@
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gradio==3.39.0
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numpy==1.23.3
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tensorflow==2.9.1
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gradio==3.39.0
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numpy==1.23.3
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#tensorflow==2.9.1
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