From 3245bc50f4c76c1abe82593d763b29f31eb65523 Mon Sep 17 00:00:00 2001
From: Daniel Saavedra <dlsaavedra@uc.cl>
Date: Mon, 13 Jul 2020 21:32:35 -0400
Subject: [PATCH] Create README_Result.md

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+# Result Photovoltaic fault detector
+
+## Panel Detector
+### SDD7
+On folder [Result ssd7 panel](Result_ssd7_panel/) show code (jupyter notebook), weight and result of this model (mAP 89.8%).
+
+<p align="center">
+  <img width="800" height="400" src="Result_ssd7_panel/result_ssd7_panel/DJI_0020.jpg">
+</p>
+<p align="center">
+  <img width="800" height="400" src="Result_ssd7_panel/result_ssd7_panel/DJI_0110.jpg">
+</p>
+
+
+
+### YOLO3
+On folder [Result yolo3 panel](Result_yolo3_panel/)  weight and result of this model (mAP 86.3%).
+
+<p align="center">
+  <img width="460" height="300" src="Result_yolo3_panel/Mision%203_DJI_0045.jpg">
+</p>
+
+
+
+## Soiling Fault Detector
+### SSD300
+On folder [Result ssd300 fault 1](Result_ssd300_fault_1/) show code (jupyter notebook), weight and result of this model (mAP 79.5%).
+
+<p align="center">
+  <img width="800" height="400" src="Result_ssd300_fault_1/result_ssd300_fault_1/Mision_11_DJI_0011.jpg">
+</p>
+
+
+### YOLO3
+On folder [Result yolo3 fault 1](Result_yolo3_fault_1/) show [history train](Result_yolo3_fault_1/yolo3_full_yolo.output), weight and result of this model (mAP 73.02%).
+
+<p align="center">
+  <img width="460" height="300" src="Result_yolo3_fault_1/result_yolo3_fault_1/Mision_11_DJI_0011.jpg">
+</p>
+
+
+## Affected Cell Detector
+### YOLO3
+On folder [Result yolo3 fault 2](Result_yolo3_fault_2/) show [history train](Result_yolo3_fault_2/yolo3_full_yolo.output), weight and result of this model (mAP 71.93%).
+
+
+<p align="center">
+  <img width="460" height="300" src="Result_yolo3_fault_2/result_yolo3_fault_2/Mision%2010_DJI_0093.jpg">
+</p>
+
+
+## Diode Fault Detector
+### YOLO3
+On folder [Result yolo3 fault 4](Result_yolo3_fault_4/) show [history train](Result_yolo3_fault_4/yolo3_full_yolo.output), weight and result of this model (mAP 66.22%).
+
+
+<p align="center">
+  <img width="460" height="300" src="Result_yolo3_fault_4/result_yolo3_fault_4/Mision%2041_DJI_0044.jpg">
+</p>
+
+
+
+
+
+## Panel Disconnect Detector
+### YOLO3
+To use the detector we must only use 'panel_yolo3_disconnect.py' with the previously established form, that is:
+`python predict_yolo3_disconnect.py -c config_full_yolo_panel_infer.json -i /path/to/image/ -o /path/output/result`
+To use this model, only the yolo3_panel detector model is needed.
+
+<p align="center">
+  <img width="460" height="300" src="Result_yolo3_panel/Mision%2011_DJI_0058.jpg">
+</p>
+
+
+The idea to detect the disconnection is by calculating the luminosity of each panel, to then normalize this data and highlight the panels with a luminosity out of normality.