fix the links to different files

app.py

@@ -411,6 +411,7 @@ outputs = [gr_image_output,out_smpl_npy_download]
 
 
 ##############################################
+# %% 
 # User interace: description
 gr_title = "megadetdlc TRIALLING"
 gr_description = "Contributed by Sofia Minano, Neslihan Wittek, Nirel Kadzo, VicShaoChih Chiang -- DLC AI Residents 2022..\
@@ -427,9 +428,10 @@ demo = gr.Interface(predict_pipeline,
                     outputs=outputs, 
                     title=gr_title, 
                     description=gr_description,
-                    examples=examples,
                     theme="huggingface",
                     #live=True
                     )
 
 demo.launch(enable_queue=True, share=True)
+
+# %%

dlcmodel/models.py

@@ -33,7 +33,7 @@ def DownloadModel(modelname, target_dir):
                 member.path = member.path[l:]
                 yield member
 
-    neturls = read_plainconfig("/dlcmodel/pretrained_model_urls.yaml") #FIXME
+    neturls = read_plainconfig("dlcmodel/pretrained_model_urls.yaml") #FIXME
     
     if modelname in neturls.keys():
         url = neturls[modelname]

save_results.py

@@ -0,0 +1,56 @@
+import json 
+import numpy as np
+import pdb
+
+dict_pred = {0: 'animal', 1: 'person', 2: 'vehicle'}
+
+
+def save_results(md_results, dlc_outputs,map_label_id_to_str,thr,output_file = 'dowload_predictions.json'):
+
+    """
+    write json
+    """
+    info = {}
+    ## info megaDetector
+    info['file']= md_results.files[0]
+    number_bb = len(md_results.xyxy[0].tolist())
+    info['number_of_bb'] = number_bb
+    number_bb_thr = len(dlc_outputs)
+    labels = [n for n in map_label_id_to_str.values()]
+    #pdb.set_trace()
+    new_index = []
+    for i in range(number_bb):
+        corner_x1,corner_y1,corner_x2,corner_y2,confidence, _ =  md_results.xyxy[0].tolist()[i]
+
+        if confidence > thr:
+            new_index.append(i)
+
+
+    for i in range(number_bb_thr):
+        aux={}
+        corner_x1,corner_y1,corner_x2,corner_y2,confidence, _ =  md_results.xyxy[0].tolist()[new_index[i]]
+        aux['corner_1'] = (corner_x1,corner_y1)
+        aux['corner_2'] = (corner_x2,corner_y2)
+        aux['predict MD'] = md_results.names[0]
+        aux['confidence MD'] = confidence
+        
+        ## info dlc
+        kypts = []
+        pdb.set_trace()
+        for s in dlc_outputs[i]:
+            #print(s)
+            aux1 = []
+            for j in s:
+                aux1.append(float(j))
+
+            kypts.append(aux1)
+        pdb.set_trace()
+        aux['dlc_pred']  = dict(zip(labels,kypts))
+        info['bb_' + str(new_index[i]) ]=aux
+
+
+    with open(output_file, 'w') as f:
+        json.dump(info, f, indent=1)
+        print('Output file saved at {}'.format(output_file))
+
+    return output_file