feat: pictures as a gallery

app/assets/config/{config_df.json → config_fields.json}

@@ -1,6 +1,5 @@
 {
-    "headers": [
-        "image",
+    "fields": [
         "latitude",
         "longitude",
         "wounded", 
@@ -15,6 +14,7 @@
         "physical_changes_body",
         "physical_changes_head", 
         "physical_changes_feathers", 
-        "physical_changes_legs"
+        "physical_changes_legs",
+        "image"
     ]
 }

app/main_multianimal.py

@@ -1,9 +1,8 @@
 import gradio as gr
 from gradio_modal import Modal
 
-from utils_df import get_headers
 from utils_json import *
-from utils_df import save_individual_to_df, get_headers, save_and_rest_df
+from utils_df import save_individual_to_gallery
 from maps import get_location
 from functools import partial
 from dead import show_section_dead
@@ -17,11 +16,16 @@ from style import *
 from theme import theme, css
 
 with gr.Blocks(theme=theme, css=css) as demo:
+    create_json_all_individuals()
     with gr.Row(): 
         show_modal = gr.Button("Add an Animal", scale=3)
         submit_button = gr.Button("Submit All Animals", scale=1)
-    df = gr.Dataframe(headers=get_headers(),
-                      visible=False)
+    # df = gr.Dataframe(headers=get_headers(),
+    #                   visible=False)
+    gallery = gr.Gallery(
+        label="Gallery of Records", elem_id="gallery", 
+        columns=[1], rows=[1],
+        object_fit="contain", height="auto", interactive=False)
     with Modal(visible=False) as modal:
         # ---------------------------------------------------------
         # Intro Text
@@ -33,9 +37,11 @@ with gr.Blocks(theme=theme, css=css) as demo:
         # ---------------------------------------------------------
         # Camera
         with gr.Row():
-            #with gr.Column(scale=1):
+            def save_image(camera):
+                add_data_to_individual("image", camera.tolist())
+
             camera = gr.Image(elem_id="image")
-                
+            camera.input(save_image, inputs=[camera])
         # ---------------------------------------------------------
         # Location
         #with gr.Row():
@@ -187,6 +193,7 @@ with gr.Blocks(theme=theme, css=css) as demo:
             button_df = gr.Button("Submit Animal Report", scale = 3)
             button_clear = gr.ClearButton(scale = 1, 
                                           components=[
+                camera,
                 location, identified_location, 
                 button_collision_dead, button_deliberate_destruction_dead, button_indirect_destruction_dead, button_natural_cause_dead, 
                 dropdown_dead, dropdown_level2_dead, openfield_level2_dead, dropdown_extra_level2_dead,
@@ -201,17 +208,20 @@ with gr.Blocks(theme=theme, css=css) as demo:
         button_clear.click()
         button_clear.click(hide_physical,
                            outputs=[checkbox_beak, text_beak, checkbox_body, text_body, checkbox_feathers, text_feathers, checkbox_head, text_head, checkbox_legs, text_legs])
-        button_df.click(save_individual_to_df, 
-                        inputs=[df],
-                        outputs=[df])
+        # button_df.click(save_individual_to_df, 
+        #                 inputs=[df],
+        #                 outputs=[df])
+        button_df.click(save_individual_to_gallery, 
+                        inputs=[gallery],
+                        outputs=[gallery])
         button_df.click(lambda: Modal(visible=False), None, modal)
     
     # ---------------------------------------------------------
     # Event Functions of the landing page buttons
     show_modal.click(lambda: Modal(visible=True), None, modal)
-    show_modal.click(create_json)
-    submit_button.click(save_and_rest_df, inputs=[df], outputs=[df])
-
+    show_modal.click(create_json_one_individual)
+    #submit_button.click(save_and_rest_df, inputs=[df], outputs=[df])
+    #submit_button.click(save_individual_to_gallery)
 
 
      

app/utils_df.py

@@ -1,8 +1,9 @@
 import gradio as gr
 import pandas as pd
+import numpy as np
 from dotenv import load_dotenv
 from utils_config import load_config
-from utils_json import get_json_one_individual, save_all_animals
+from utils_json import get_json_one_individual, save_to_all_individuals
 import os
 load_dotenv()
 PATH = os.getcwd() + "/"
@@ -10,35 +11,133 @@ PATH_ASSETS = os.getenv('PATH_ASSETS')
 PATH_CONFIG = PATH + PATH_ASSETS + "config/"
 
 def get_headers(): 
-    headers_config = load_config(PATH_CONFIG + "config_df.json")
+    headers_config = load_config(PATH_CONFIG + "config_headers.json")
     headers = headers_config["headers"]
     return headers
 
-def match_data_to_headers(headers, one_individual): 
+def get_fields(): 
+    fields_config = load_config(PATH_CONFIG + "config_fields.json")
+    fields = fields_config["fields"]
+    return fields
+
+def match_data_to_fields(fields, one_individual): 
     new_row = {}
-    for key in headers:
+    for key in fields:
         if key in one_individual:
-            if type(one_individual[key])==list:
+            if key=="image": 
+                new_row[key] = one_individual[key]
+            elif type(one_individual[key])==list:
                 new_row[key] = ' , '.join(one_individual[key])
             else:
                 new_row[key] = one_individual[key]
         else:
             new_row[key] = "NA"
-    return list(new_row.values())
+    return new_row
+
+def process_animals(all_animals): 
+    processed_animals = []
+    print(len(all_animals))
+    for _, animal in all_animals.items(): 
+        image = np.array(animal["image"])
+        caption = []
+        for key, val in animal.items(): 
+            if key!="image": 
+                if key=="latitude": 
+                    caption.extend([
+                        " | Latitude: " + str(animal["latitude"])])
+                elif key=="longitude": 
+                    caption.extend([
+                        " | Longitude: " + str(animal["longitude"])])
+                elif key=="wounded" and val=="True": 
+                    caption.extend([" | Wounded: " + animal["wounded"]])
+                elif key=="dead" and val=="True":
+                    caption.extend([" | Dead: " + animal["dead"]])
+                elif key=="circumstance": 
+                    caption.extend([" | Circumstances: " , 
+                                    animal["circumstance"],
+                                    animal["circumstance_dropdown_level1"], 
+                                    animal["circumstance_dropdown_level2"],
+                                    animal["circumstance_openfield_level2"], 
+                                    animal["circumstance_dropdown_extra_level2"]])
+                elif key=="behavior": 
+                    caption.extend([" | Behavior: ", animal[key]])
+                elif "physical_changes" in key:
+                    if not(" | Physical Changes: " in caption) :
+                        caption.extend([" | Physical Changes: ",
+                                        "Beak: " + animal["physical_changes_beak"],
+                                        "Body: " + animal["physical_changes_body"], 
+                                        "Head: " + animal["physical_changes_head"],
+                                        "Feathers: " + animal["physical_changes_feathers"], 
+                                        "Legs: " + animal["physical_changes_legs"]])
+        caption_str = " ".join(caption)
+        animal = (image, caption_str)
+        processed_animals.append(animal)
+    return processed_animals
 
-def save_individual_to_df(df): 
-    headers = get_headers()
+def set_gallery_size(len_animals): 
+    if len_animals < 10: 
+        num_cols=5
+        num_rows=2
+    else: 
+        num_cols = len_animals/2
+        num_rows = len_animals/(num_cols)
+    return num_cols, num_rows
+
+def save_individual_to_gallery(gallery):
     one_individual = get_json_one_individual()
-    new_row = match_data_to_headers(headers, one_individual)
-    new_row_df = pd.DataFrame([new_row], columns=headers)  
-    df_new = pd.concat([df, new_row_df], ignore_index=True)
-    df_gr = gr.DataFrame(visible=True,
-                         value=df_new,
-                         headers=headers)
-    return df_gr
-
-def save_and_rest_df(df):
-    save_all_animals(df)
-    df = gr.Dataframe(headers=get_headers(),
-                      visible=False)
-    return df
+    fields = get_fields()
+    one_individual_matched = match_data_to_fields(fields, one_individual)
+    all_animals = save_to_all_individuals(one_individual_matched)
+    num_cols, num_rows = set_gallery_size(len(all_animals))
+    processed_animals = process_animals(all_animals)
+    gallery = gr.Gallery(
+        label="Gallery of Records", elem_id="gallery", 
+        columns=[num_cols], rows=[num_rows],
+        value=processed_animals,
+        object_fit="contain", height="auto", interactive=False)
+    return gallery
+    
+# def save_individual_to_df(df): 
+#     fields = get_fields()
+#     one_individual = get_json_one_individual()
+#     headers = get_headers()
+#     new_row = match_data_to_fields(fields, one_individual)
+#     new_row = format_row(new_row, headers)
+#     new_row_df = pd.DataFrame([new_row], columns=headers)  
+#     df_new = pd.concat([df, new_row_df], ignore_index=True)
+#     df_gr = gr.DataFrame(visible=True,
+#                          value=df_new,
+#                          headers=headers)
+#     return df_gr
+
+# def save_and_rest_df(df):
+#     save_all_animals(df)
+#     df = gr.Dataframe(fields=get_fields(),
+#                       visible=False)
+#     return df
+
+# def format_row(new_row, headers):
+#     formatted_row = {}
+#     #formatted_row["image"] = new_row["image"]
+#     for header in headers: 
+#         if header=="location": 
+#             formatted_row[header] = " | ".join(["Latitude: " + str(new_row["latitude"]), 
+#                                                 "Longitude: " + str(new_row["longitude"])])
+#         elif header=="state": 
+#             formatted_row[header] = " | ".join(["Wounded: " + new_row["wounded"], 
+#                                                 "Dead: " + new_row["dead"]])
+#         elif header=="circumstance": 
+#             formatted_row[header] = " | ".join([new_row["circumstance"],
+#                                                 new_row["circumstance_dropdown_level1"], 
+#                                                 new_row["circumstance_dropdown_level2"],
+#                                                 new_row["circumstance_openfield_level2"], 
+#                                                 new_row["circumstance_dropdown_extra_level2"]])
+#         elif header=="behavior": 
+#             formatted_row[header] = new_row[header]
+#         elif header=="physical_changes":
+#             formatted_row[header] = " | ".join([new_row["physical_changes_beak"],
+#                                                 new_row["physical_changes_body"], 
+#                                                 new_row["physical_changes_head"],
+#                                                 new_row["physical_changes_feathers"], 
+#                                                 new_row["physical_changes_legs"]])
+#     return list(formatted_row.values())

app/utils_json.py

@@ -1,26 +1,42 @@
 import json
 import gradio as gr
 
-def create_json(one_individual={}):
+def create_json_one_individual(one_individual={}):
     # Serializing json
     one_individual = json.dumps(one_individual)
     with open("data/one_individual.json", "w") as outfile:
         outfile.write(one_individual)
+def create_json_all_individuals(all_individuals={}):
+    all_individuals = json.dumps(all_individuals)
+    with open("data/all_individuals.json", "w") as outfile:
+        outfile.write(all_individuals)
 
 def add_data_to_individual(key, value): 
     with open("data/one_individual.json", 'r') as openfile:
         one_individual = json.load(openfile)
     one_individual[key] = value
-    create_json(one_individual)
+    create_json_one_individual(one_individual)
 
 def get_json_one_individual():
     with open("data/one_individual.json", 'r') as openfile:
         one_individual = json.load(openfile)
     return one_individual
 
+def get_json_all_individuals():
+    with open("data/all_individuals.json", "r") as openfile:
+        all_individuals = json.load(openfile)
+    return all_individuals
 
-def save_all_animals(df):
-    all_animals = df.to_json(orient="records")
-    with open("data/all_animals.json", "w") as outfile:
-        outfile.write(all_animals)
+def save_to_all_individuals(one_individual):
+    all_individuals = get_json_all_individuals()
+    all_individuals[str(len(all_individuals))] = one_individual
+    all_individuals_for_json = json.dumps(all_individuals)
+    with open("data/all_individuals.json", "w") as outfile:
+        outfile.write(all_individuals_for_json)
+    return all_individuals
+
+# def save_all_individuals(df):
+#     all_individuals = df.to_json(orient="records")
+#     with open("data/all_individuals.json", "w") as outfile:
+#         outfile.write(all_individuals)