add requirement

code/app.py

@@ -14,7 +14,7 @@ from gradio_utils import read_video
 
 
 fece_detection = FaceDetection()
-csv_url = './ippg_predict.csv'
+csv_url = './code/ippg_predict.csv'
 
 
 def video_to_rppg_dynamic(model_choice,path):
@@ -25,9 +25,9 @@ def video_to_rppg_dynamic(model_choice,path):
     '''
     print(model_choice,"=======================================")
     if model_choice=="ContrastPhys":
-        model = PhysNet_Model('./contrast_phys/model_weights.pt')
+        model = PhysNet_Model('./code/contrast_phys/model_weights.pt')
     elif model_choice=="DeepPhys":
-        model = DeepPhys_Model('./contrast_phys/PURE_PURE_UBFC_deepphys_Epoch29.pth')
+        model = DeepPhys_Model('./code/contrast_phys/PURE_PURE_UBFC_deepphys_Epoch29.pth')
     else:
         model = None
 

code/physiological_indicators.py

@@ -42,7 +42,7 @@ class PhysiologicalIndicators:
         ippg_data = np.array(ippg_data).reshape(len(ippg_data),1)
 
         bp_pred = []
-        model_list = joblib.load( './model_weight/lgb_model_ppg2bp.pkl')
+        model_list = joblib.load( './code/model_weight/lgb_model_ppg2bp.pkl')
         for model in model_list:
             result = model.predict(ippg_data)
             bp_pred.append(result+10)

code/utils_sig.py

@@ -238,7 +238,7 @@ def RGB_HR(ROI_list):
     # ippg_chanel_data = np.array(ippg_chanel_data).reshape(len(ippg_chanel_data),6)
 
     HR_pred = []
-    model_list = joblib.load( './model_weight/lgb_model_threechanel2HR.pkl')
+    model_list = joblib.load( './code/model_weight/lgb_model_threechanel2HR.pkl')
     for model in model_list:
         result = model.predict(ippg_chanel_data)
         HR_pred.append(result+10)