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"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING:absl:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
]
}
],
"source": [
"from tensorflow.keras.models import load_model\n",
"\n",
"# tải mô hình \n",
"model = load_model('cnn_cats_dogs.h5')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"70"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"\n",
"cats_path = 'test/cats'\n",
"dogs_path = 'test/dogs'\n",
"\n",
"cats_path_list = os.listdir(cats_path)\n",
"dogs_path_list = os.listdir(dogs_path)\n",
"len(dogs_path_list)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 31ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 31ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 63ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 43ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 31ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 35ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 34ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 36ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 33ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n",
"\u001b[1m1/1\u001b[0m \u001b[32mββββββββββββββββββββ\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 37ms/step\n",
"Sα» αΊ£nh dα»± ΔoΓ‘n ΔΓΊng nhΓ£n con mΓ¨o lΓ : 50/70 αΊ£nh\n",
"Sα» αΊ£nh dα»± ΔoΓ‘n ΔΓΊng nhΓ£n con chΓ³ lΓ : 48/70 αΊ£nh\n",
"Accuracy: 0.7\n"
]
}
],
"source": [
"from tensorflow.keras.preprocessing import image\n",
"import numpy as np\n",
"\n",
"cats_size = len(cats_path_list)\n",
"dogs_size = len(dogs_path_list)\n",
"correct_cats = 0\n",
"correct_dogs = 0\n",
"\n",
"for path in cats_path_list:\n",
" full_path = os.path.join(cats_path, path)\n",
" img = image.load_img(full_path, target_size=(150,150))\n",
" img_array = image.img_to_array(img)\n",
" img_array = np.expand_dims(img_array, axis=0)\n",
" img_array /= 255.0\n",
" prediction = model.predict(img_array)\n",
" if (prediction < 0.5):\n",
" correct_cats += 1\n",
"\n",
"for path in dogs_path_list:\n",
" full_path = os.path.join(dogs_path, path)\n",
" img = image.load_img(full_path, target_size=(150,150))\n",
" img_array = image.img_to_array(img)\n",
" img_array = np.expand_dims(img_array, axis=0)\n",
" img_array /= 255.0\n",
" prediction = model.predict(img_array)\n",
" if (prediction > 0.5):\n",
" correct_dogs += 1\n",
"\n",
"model_accuracy = (correct_cats + correct_dogs) / (cats_size + dogs_size)\n",
"\n",
"print(f\"Sα» αΊ£nh dα»± ΔoΓ‘n ΔΓΊng nhΓ£n con mΓ¨o lΓ : {correct_cats}/{cats_size} αΊ£nh\")\n",
"print(f\"Sα» αΊ£nh dα»± ΔoΓ‘n ΔΓΊng nhΓ£n con chΓ³ lΓ : {correct_dogs}/{dogs_size} αΊ£nh\")\n",
"print(f\"Accuracy: {model_accuracy}\")"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"12.22\n"
]
}
],
"source": [
"import numpy as np\n",
"\n",
"c = 12.222222\n",
"print(np.round(c, 2))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|