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| Author | SHA1 | Date | |
|---|---|---|---|
|
26acdd7c67 |
1
.gitignore
vendored
1
.gitignore
vendored
@@ -8,7 +8,6 @@ Train&Test_4/
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Train&Test_D/
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Train&Test_C/
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Train&Test_A/
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Train&Test_A2/
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Train&Test_S/
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result_ssd7_panel_cell/
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Thermal/
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File diff suppressed because one or more lines are too long
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@@ -239,7 +239,7 @@ def rgb2hsv(rgb):
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def doubleMADsfromMedian(y,thresh=3.5):
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# warning: this function does not check for NAs
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# nor does it address issues when
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# nor does it address issues when
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# more than 50% of your data have identical values
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m = np.median(y)
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abs_dev = np.abs(y - m)
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@@ -255,7 +255,7 @@ def doubleMADsfromMedian(y,thresh=3.5):
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def watershed_marked(thresh, min_Area = 100, threshold_median_Area = 3):
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## Thresh is the segmentation image use to watershed
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##
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# Perform the distance transform algorithm
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dist = cv2.distanceTransform(thresh, cv2.DIST_L2, 3)
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# Normalize the distance image for range = {0.0, 1.0}
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@@ -300,14 +300,14 @@ def watershed_marked(thresh, min_Area = 100, threshold_median_Area = 3):
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for i,Logic in zip(Areas[:,0], L_Areas) :
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if Logic:
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markers[markers == i] = 0
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return Areas[L_Areas,:], dist_8u,markers
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def pixel2gps(points, geot):
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# transform pixel to gps coordinate
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return np.vstack(gr.map_pixel_inv(points[:,1], points[:,0],geot[1],geot[-1], geot[0],geot[3])).T
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def gps2pixel(points_coord, geot):
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# transform gps coordinate to pixel
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@@ -9,8 +9,4 @@ matplotlib==3.2.2
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scipy==1.4.1
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ipython==7.19.0
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scikit_learn==0.23.2
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geopandas
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rtree==0.9.3
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simplekml
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urbanaccess pandana
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cenpy
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@@ -1,4 +1,3 @@
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original: https://github.com/RentadroneCL/Photovoltaic_Fault_Detector
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# Photovoltaic Fault Detector
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@@ -7,11 +6,11 @@ original: https://github.com/RentadroneCL/Photovoltaic_Fault_Detector
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[](https://www.codetriage.com/rentadronecl/photovoltaic_fault_detector)
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[](https://coveralls.io/github/RentadroneCL/Photovoltaic_Fault_Detector)
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[SimpleMap.io](https://simplemap.io/)
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[Rentadrone.cl](https://rentadronecl.github.io)
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## Forum
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This project is part of the [UNICEF Innovation Fund Discourse community](https://unicef-if.discourse.group/c/projects/rentadrone/10). You can post comments or questions about each category of [SimpleMap.io Open-Source Initiative](https://rentadronecl.github.io) algorithms. We encourage users to participate in the forum and to engage with fellow users.
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This project is part of the [UNICEF Innovation Fund Discourse community](https://unicef-if.discourse.group/c/projects/rentadrone/10). You can post comments or questions about each category of [Rentadrone Developers](https://rentadrone.cl/developers/) algorithms. We encourage users to participate in the forum and to engage with fellow users.
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## Summary
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@@ -210,7 +209,7 @@ The configuration file for SSD300 is a json file, which looks like this (exampl
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`python train_ssd.py -c config.json -o /path/to/result`
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or
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`python train_yolo.py -c config.json -o /path/to/result`
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`python train_ssd.py -c config.json -o /path/to/result`
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By the end of this process, the code will write the weights of the best model to file best_weights.h5 (or whatever name specified in the setting "saved_weights_name" in the config.json file). The training process stops when the loss on the validation set is not improved in 20 consecutive epoches.
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@@ -265,5 +264,6 @@ Before sending your pull requests, make sure you followed this list.
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- Read [Code of Conduct](CODE_OF_CONDUCT.md).
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- Check if my changes are consistent with the [guidelines](https://github.com/RentadroneCL/model-definition/blob/master/CONTRIBUTING.md#general-guidelines-and-philosophy-for-contribution).
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- Changes are consistent with the [Coding Style](https://github.com/RentadroneCL/model-definition/blob/master/CONTRIBUTING.md#c-coding-style).
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- Run [Unit Tests](https://github.com/RentadroneCL/model-definition/CONTRIBUTING.md#running-unit-tests).
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@@ -1 +0,0 @@
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Tiempo promedio:nan
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@@ -1,29 +0,0 @@
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2020-12-14 22:27:04.267611: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory
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2020-12-14 22:27:04.267749: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory
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2020-12-14 22:27:04.267767: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
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2020-12-14 22:27:05.268036: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
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2020-12-14 22:27:05.268076: E tensorflow/stream_executor/cuda/cuda_driver.cc:351] failed call to cuInit: UNKNOWN ERROR (303)
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2020-12-14 22:27:05.268102: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (dlsaavedra-X406UAR): /proc/driver/nvidia/version does not exist
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2020-12-14 22:27:05.268334: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
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2020-12-14 22:27:05.311492: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 1800000000 Hz
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2020-12-14 22:27:05.313101: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55f4be3033d0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
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2020-12-14 22:27:05.313143: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
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WARNING:tensorflow:AutoGraph could not transform <bound method YoloLayer.call of <yolo.YoloLayer object at 0x7fb92423a8d0>> and will run it as-is.
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Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
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Cause: unexpected indent (<unknown>, line 144)
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WARNING:tensorflow:AutoGraph could not transform <bound method YoloLayer.call of <yolo.YoloLayer object at 0x7fb904726710>> and will run it as-is.
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Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
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Cause: unexpected indent (<unknown>, line 144)
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WARNING:tensorflow:AutoGraph could not transform <bound method YoloLayer.call of <yolo.YoloLayer object at 0x7fb9044f2c10>> and will run it as-is.
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Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
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Cause: unexpected indent (<unknown>, line 144)
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WARNING:tensorflow:ModelCheckpoint mode 1 is unknown, fallback to auto mode.
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WARNING:tensorflow:Model failed to serialize as JSON. Ignoring... Layers with arguments in `__init__` must override `get_config`.
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2020-12-14 22:27:16.470550: I tensorflow/core/profiler/lib/profiler_session.cc:225] Profiler session started.
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2020-12-14 22:27:16.470928: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcupti.so.10.1'; dlerror: libcupti.so.10.1: cannot open shared object file: No such file or directory
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2020-12-14 22:27:16.470972: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1307] function cupti_interface_->Subscribe( &subscriber_, (CUpti_CallbackFunc)ApiCallback, this)failed with error CUPTI could not be loaded or symbol could not be found.
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2020-12-14 22:27:16.470988: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1346] function cupti_interface_->ActivityRegisterCallbacks( AllocCuptiActivityBuffer, FreeCuptiActivityBuffer)failed with error CUPTI could not be loaded or symbol could not be found.
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2020-12-14 22:27:20.300351: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1329] function cupti_interface_->EnableCallback( 0 , subscriber_, CUPTI_CB_DOMAIN_DRIVER_API, cbid)failed with error CUPTI could not be loaded or symbol could not be found.
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2020-12-14 22:27:20.300441: I tensorflow/core/profiler/internal/gpu/device_tracer.cc:88] GpuTracer has collected 0 callback api events and 0 activity events.
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2020-12-14 22:28:18.604124: W tensorflow/core/kernels/data/generator_dataset_op.cc:103] Error occurred when finalizing GeneratorDataset iterator: Cancelled: Operation was cancelled
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2020-12-14 22:29:29.713989: W tensorflow/core/kernels/data/generator_dataset_op.cc:103] Error occurred when finalizing GeneratorDataset iterator: Cancelled: Operation was cancelled
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@@ -1,22 +0,0 @@
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Seen labels: {'panel': 854}
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Given labels: ['panel']
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Training on: ['panel']
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multi_gpu:1
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Loading pretrained weights.
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Train for 12 steps, validate for 1 steps
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Epoch 1/2
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Epoch 00001: loss improved from inf to 40.76296, saving model to Result_yolo3_panel2/yolo3_full_panel.h5
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12/12 - 68s - loss: 40.7630 - yolo_layer_loss: 12.8884 - yolo_layer_1_loss: 27.8505 - yolo_layer_2_loss: 0.0241 - val_loss: 3793.7336 - val_yolo_layer_loss: 1322.7670 - val_yolo_layer_1_loss: 2470.9607 - val_yolo_layer_2_loss: 0.0060
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Epoch 2/2
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Epoch 00002: loss did not improve from 40.76296
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12/12 - 71s - loss: 46.9910 - yolo_layer_loss: 20.9780 - yolo_layer_1_loss: 26.0097 - yolo_layer_2_loss: 0.0033 - val_loss: 72523.8125 - val_yolo_layer_loss: 4534.5332 - val_yolo_layer_1_loss: 67989.2812 - val_yolo_layer_2_loss: 0.0000e+00
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94 instances of class panel with average precision: 0.0000
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mAP using the weighted average of precisions among classes: 0.0000
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mAP: 0.0000
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@@ -1,11 +0,0 @@
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2020-12-14 22:29:36.919265: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory
|
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2020-12-14 22:29:36.919408: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory
|
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2020-12-14 22:29:36.919425: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
|
||||
2020-12-14 22:29:38.653634: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
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2020-12-14 22:29:38.653676: E tensorflow/stream_executor/cuda/cuda_driver.cc:351] failed call to cuInit: UNKNOWN ERROR (303)
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||||
2020-12-14 22:29:38.653711: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (dlsaavedra-X406UAR): /proc/driver/nvidia/version does not exist
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||||
2020-12-14 22:29:38.653939: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
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||||
2020-12-14 22:29:38.678825: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 1800000000 Hz
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||||
2020-12-14 22:29:38.679672: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5569ee6e0e00 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
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2020-12-14 22:29:38.679731: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
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WARNING:tensorflow:No training configuration found in save file: the model was *not* compiled. Compile it manually.
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@@ -1,4 +0,0 @@
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dict_items([(0, (0.0, 94.0))])
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94 instances of class panel with average precision: 0.0000
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mAP using the weighted average of precisions among classes: 0.0000
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mAP: 0.0000
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@@ -1,49 +0,0 @@
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{
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"model" : {
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"min_input_size": 400,
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"max_input_size": 400,
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"anchors": [0,0, 0,0, 0,0, 4,175, 4,92, 5,92, 6,190, 7,87, 30,5],
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"labels": ["panel"],
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"backend": "keras-yolo3-master/full_yolo_backend.h5"
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},
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"train": {
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"train_image_folder": "Train&Test_A2/Train/images/",
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"train_annot_folder": "Train&Test_A2/Train/anns/",
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"cache_name": "Result_yolo3_panel2/train_panel.pkl",
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"train_times": 3,
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|
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"batch_size": 2,
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"learning_rate": 1e-3,
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"nb_epochs": 500,
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"warmup_epochs": 15,
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"ignore_thresh": 0.5,
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"gpus": "0",
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|
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"grid_scales": [1,1,1],
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"obj_scale": 5,
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"noobj_scale": 1,
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"xywh_scale": 1,
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"class_scale": 1,
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|
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"tensorboard_dir": "Result_yolo3_panel2/log_experimento_panel_gpu",
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"saved_weights_name": "Result_yolo3_panel2/yolo3_full_panel.h5",
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"debug": true
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},
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"valid": {
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"valid_image_folder": "Train&Test_A2/Train/images/",
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"valid_annot_folder": "Train&Test_A2/Train/anns/",
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"cache_name": "Result_yolo3_panel2/val_panel_2.pkl",
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"valid_times": 1
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},
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"test": {
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"test_image_folder": "Train&Test_A2/Train/images/",
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"test_annot_folder": "Train&Test_A2/Train/anns/",
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"cache_name": "Result_yolo3_panel2/test_panel_2.pkl",
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"test_times": 1
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}
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}
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@@ -1,49 +0,0 @@
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{
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||||
"model" : {
|
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"min_input_size": 400,
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"max_input_size": 400,
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||||
"anchors": [0,0, 0,0, 0,0, 4,175, 4,92, 5,92, 6,190, 7,87, 30,5],
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"labels": ["panel"],
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"backend": "keras-yolo3-master/full_yolo_backend.h5"
|
||||
},
|
||||
|
||||
"train": {
|
||||
"train_image_folder": "Train&Test_A2/Train/images/",
|
||||
"train_annot_folder": "Train&Test_A2/Train/anns/",
|
||||
"cache_name": "Result_yolo3_panel2/train_panel.pkl",
|
||||
|
||||
"train_times": 3,
|
||||
|
||||
"batch_size": 2,
|
||||
"learning_rate": 1e-3,
|
||||
"nb_epochs": 2,
|
||||
"warmup_epochs": 15,
|
||||
"ignore_thresh": 0.5,
|
||||
"gpus": "0",
|
||||
|
||||
"grid_scales": [1,1,1],
|
||||
"obj_scale": 5,
|
||||
"noobj_scale": 1,
|
||||
"xywh_scale": 1,
|
||||
"class_scale": 1,
|
||||
|
||||
"tensorboard_dir": "Result_yolo3_panel2/log_experimento_panel_gpu",
|
||||
"saved_weights_name": "Result_yolo3_panel2/yolo3_full_panel.h5",
|
||||
"debug": true
|
||||
},
|
||||
|
||||
"valid": {
|
||||
"valid_image_folder": "Train&Test_A2/Test/images/",
|
||||
"valid_annot_folder": "Train&Test_A2/Test/anns/",
|
||||
"cache_name": "Result_yolo3_panel2/val_panel.pkl",
|
||||
|
||||
"valid_times": 1
|
||||
},
|
||||
"test": {
|
||||
"test_image_folder": "Train&Test_A2/Test/images/",
|
||||
"test_annot_folder": "Train&Test_A2/Test/anns/",
|
||||
"cache_name": "Result_yolo3_panel2/test_panel.pkl",
|
||||
|
||||
"test_times": 1
|
||||
}
|
||||
}
|
||||
@@ -272,7 +272,11 @@ def _main_(args):
|
||||
callbacks = callbacks
|
||||
)
|
||||
|
||||
train_model.load_weights(config['train']['saved_weights_name'])
|
||||
|
||||
# make a GPU version of infer_model for evaluation
|
||||
#if multi_gpu > 1:
|
||||
# infer_model = load_model(config['train']['saved_weights_name'])
|
||||
infer_model.load_weights(config['train']['saved_weights_name'])
|
||||
infer_model.save(config['train']['saved_weights_name'])
|
||||
###############################
|
||||
# Run the evaluation
|
||||
|
||||
@@ -4,14 +4,14 @@ gast==0.2.2
|
||||
grpcio
|
||||
h5py
|
||||
Markdown
|
||||
numpy==1.22
|
||||
numpy
|
||||
opencv-contrib-python
|
||||
opt-einsum
|
||||
protobuf
|
||||
PyYAML
|
||||
scipy
|
||||
six
|
||||
tensorflow==2.7.2
|
||||
tensorflow==2.4.0
|
||||
termcolor
|
||||
tqdm
|
||||
Werkzeug
|
||||
|
||||
Reference in New Issue
Block a user