diff --git a/src/live.py b/src/live.py index 9e762f5..3951c67 100644 --- a/src/live.py +++ b/src/live.py @@ -13,26 +13,25 @@ import utils RESIZED_SIZE = (100, 50, 3) LABELS = ['octane', 'werewolf', 'breakout', 'aftershock'] +MODELS_PATH = '../models' +MODEL_FILENAME = 'rot_25e' + # Load model -model = models.load_model('../models/model') +model = models.load_model(MODELS_PATH + '/' + MODEL_FILENAME) utils.startup(need_focus=False) running = True while running: - utils.screenshot(filename='live', folder='../models') + utils.screenshot(filename='live', folder=MODELS_PATH) # Lecture de l'image - img = PIL.Image.open('../models/live') - - # print(f"img.size = {img.size}") + img = PIL.Image.open(MODELS_PATH + '/live') # Redimensionnement de l'image img = img.resize(RESIZED_SIZE[:-1], PIL.Image.ANTIALIAS) - # print(f"img.size = {img.size}") - X = np.asarray(img) Y = model.evaluate(X) diff --git a/src/notebook.ipynb b/src/notebook.ipynb index fffbf52..d000df8 100644 --- a/src/notebook.ipynb +++ b/src/notebook.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -17,15 +17,18 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "/tmp/deepl/dataset_rot\n", - "['octane', 'werewolf', 'breakout', 'aftershock']\n" + "ename": "StopIteration", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mStopIteration\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/home/damien/GitHub/DeepLearning/src/notebook.ipynb Cell 2'\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m DATASET_PATH \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m./dataset_rot/\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 5\u001b[0m DATASET_PATH \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mabspath(DATASET_PATH)\n\u001b[0;32m----> 6\u001b[0m CLASSES \u001b[39m=\u001b[39m \u001b[39mnext\u001b[39;49m(os\u001b[39m.\u001b[39;49mwalk(DATASET_PATH))[\u001b[39m1\u001b[39m]\n\u001b[1;32m 8\u001b[0m \u001b[39mprint\u001b[39m(DATASET_PATH)\n\u001b[1;32m 9\u001b[0m \u001b[39mprint\u001b[39m(CLASSES)\n", + "\u001b[0;31mStopIteration\u001b[0m: " ] } ], @@ -43,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -89,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -133,7 +136,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -145,7 +148,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -267,7 +270,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -324,7 +327,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -350,7 +353,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -362,7 +365,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [ {