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eynollah config files has renamed from config.json to config_eynollah.json - training trocr model still misses to write config file into checkpoint directories

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vahidrezanezhad 2026-02-18 16:04:44 +01:00
parent b426f7f152
commit 4f66734e4d
3 changed files with 12 additions and 14 deletions
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10
src/eynollah/training/inference.py
View file

@ -740,12 +740,10 @@ class sbb_predict:
) )
def main(image, dir_in, model, patches, save, save_layout, ground_truth, xml_file, cpu, out, min_area): def main(image, dir_in, model, patches, save, save_layout, ground_truth, xml_file, cpu, out, min_area):
assert image or dir_in, "Either a single image -i or a dir_in -di is required" assert image or dir_in, "Either a single image -i or a dir_in -di is required"
try:
with open(os.path.join(model,'config_eynollah.json')) as f: with open(os.path.join(model,'config_eynollah.json')) as f:
config_params_model = json.load(f) config_params_model = json.load(f)
except:
with open(os.path.join(model,'config.json')) as f:
config_params_model = json.load(f)
task = config_params_model['task'] task = config_params_model['task']
if task != 'classification' and task != 'reading_order' and task != "cnn-rnn-ocr" and task != "trocr": if task != 'classification' and task != 'reading_order' and task != "cnn-rnn-ocr" and task != "trocr":
if image and not save: if image and not save:

12
src/eynollah/training/train.py
View file

@ -68,7 +68,7 @@ class SaveWeightsAfterSteps(Callback):
self.model.save(save_file) self.model.save(save_file)
with open(os.path.join(os.path.join(self.save_path, f"model_step_{self.step_count}"),"config.json"), "w") as fp: with open(os.path.join(os.path.join(self.save_path, f"model_step_{self.step_count}"),"config_eynollah.json"), "w") as fp:
json.dump(self._config, fp) # encode dict into JSON json.dump(self._config, fp) # encode dict into JSON
print(f"saved model as steps {self.step_count} to {save_file}") print(f"saved model as steps {self.step_count} to {save_file}")
@ -484,7 +484,7 @@ def run(
model.save(os.path.join(dir_output,'model_'+str(i))) model.save(os.path.join(dir_output,'model_'+str(i)))
with open(os.path.join(os.path.join(dir_output,'model_'+str(i)),"config.json"), "w") as fp: with open(os.path.join(os.path.join(dir_output,'model_'+str(i)),"config_eynollah.json"), "w") as fp:
json.dump(_config, fp) # encode dict into JSON json.dump(_config, fp) # encode dict into JSON
#os.system('rm -rf '+dir_train_flowing) #os.system('rm -rf '+dir_train_flowing)
@ -563,7 +563,7 @@ def run(
if i >=0: if i >=0:
model.save( os.path.join(dir_output,'model_'+str(i) )) model.save( os.path.join(dir_output,'model_'+str(i) ))
with open(os.path.join(os.path.join(dir_output,'model_'+str(i)),"config.json"), "w") as fp: with open(os.path.join(os.path.join(dir_output,'model_'+str(i)),"config_eynollah.json"), "w") as fp:
json.dump(_config, fp) # encode dict into JSON json.dump(_config, fp) # encode dict into JSON
@ -731,10 +731,10 @@ def run(
model_weight_averaged.set_weights(new_weights) model_weight_averaged.set_weights(new_weights)
model_weight_averaged.save(os.path.join(dir_output,'model_ens_avg')) model_weight_averaged.save(os.path.join(dir_output,'model_ens_avg'))
with open(os.path.join( os.path.join(dir_output,'model_ens_avg'), "config.json"), "w") as fp: with open(os.path.join( os.path.join(dir_output,'model_ens_avg'), "config_eynollah.json"), "w") as fp:
json.dump(_config, fp) # encode dict into JSON json.dump(_config, fp) # encode dict into JSON
with open(os.path.join( os.path.join(dir_output,'model_best'), "config.json"), "w") as fp: with open(os.path.join( os.path.join(dir_output,'model_best'), "config_eynollah.json"), "w") as fp:
json.dump(_config, fp) # encode dict into JSON json.dump(_config, fp) # encode dict into JSON
elif task=='reading_order': elif task=='reading_order':
@ -767,7 +767,7 @@ def run(
history = model.fit(generate_arrays_from_folder_reading_order(dir_flow_train_labels, dir_flow_train_imgs, n_batch, input_height, input_width, n_classes, thetha, augmentation), steps_per_epoch=num_rows / n_batch, verbose=1) history = model.fit(generate_arrays_from_folder_reading_order(dir_flow_train_labels, dir_flow_train_imgs, n_batch, input_height, input_width, n_classes, thetha, augmentation), steps_per_epoch=num_rows / n_batch, verbose=1)
model.save( os.path.join(dir_output,'model_'+str(i+indexer_start) )) model.save( os.path.join(dir_output,'model_'+str(i+indexer_start) ))
with open(os.path.join(os.path.join(dir_output,'model_'+str(i)),"config.json"), "w") as fp: with open(os.path.join(os.path.join(dir_output,'model_'+str(i)),"config_eynollah.json"), "w") as fp:
json.dump(_config, fp) # encode dict into JSON json.dump(_config, fp) # encode dict into JSON
''' '''
if f1score>f1score_tot[0]: if f1score>f1score_tot[0]:

4
src/eynollah/training/weights_ensembling.py
View file

@ -113,7 +113,7 @@ def run_ensembling(dir_models, out, framework):
model.load_state_dict(sd_models[0]) model.load_state_dict(sd_models[0])
os.system("mkdir "+out) os.system("mkdir "+out)
torch.save(model.state_dict(), os.path.join(out, "pytorch_model.bin")) torch.save(model.state_dict(), os.path.join(out, "pytorch_model.bin"))
os.system('cp '+os.path.join(os.path.join(dir_models,model_name) , "config.json ")+out) os.system('cp '+os.path.join(os.path.join(dir_models,model_name) , "config_eynollah.json ")+out)
else: else:
weights=[] weights=[]
@ -135,7 +135,7 @@ def run_ensembling(dir_models, out, framework):
model.set_weights(new_weights) model.set_weights(new_weights)
model.save(out) model.save(out)
os.system('cp '+os.path.join(os.path.join(dir_models,model_name) , "config.json ")+out) os.system('cp '+os.path.join(os.path.join(dir_models,model_name) , "config_eynollah.json ")+out)
@click.command() @click.command()
@click.option( @click.option(