Merge pull request #138 from banodoco/staging

Staging

backend/db_repo.py

@@ -917,6 +917,80 @@ def create_timing(self, **kwargs):
 
         return InternalResponse(payload, 'timing created successfully', True)
 
+    def bulk_create_timing(self, timing_data_list):
+        primary_image_id_list = []
+        shot_id_list = []
+        model_id_list = []
+        source_image_id_list = []
+        mask_id_list = []
+        canny_image_id_list = []
+
+        for d in timing_data_list:
+            if 'primary_image_id' in d:
+                primary_image_id_list.append(d['primary_image_id'])
+            if 'shot_id' in d:
+                shot_id_list.append(d['shot_id'])
+            if 'model_id' in d:
+                model_id_list.append(d['model_id'])
+            if 'source_image_id' in d:
+                source_image_id_list.append(d['source_image_id'])
+            if 'mask_id' in d:
+                mask_id_list.append(d['mask_id'])
+            if 'canny_image_id' in d:
+                canny_image_id_list.append(d['canny_image_id'])
+            if 'primary_image_id' in d:
+                primary_image_id_list.append(d['primary_image_id'])
+
+        primary_image_id_list = list(set(primary_image_id_list))
+        shot_id_list = list(set(shot_id_list))
+        model_id_list = list(set(model_id_list))
+        source_image_id_list = list(set(source_image_id_list))
+        mask_id_list = list(set(mask_id_list))
+        canny_image_id_list = list(set(canny_image_id_list))
+
+        file_list = InternalFileObject.objects.filter(uuid__in=primary_image_id_list + source_image_id_list + mask_id_list + canny_image_id_list, is_disabled=False).all()
+        model_list = AIModel.objects.filter(uuid__in=model_id_list, is_disabled=False).all()
+        shot_list = Shot.objects.filter(uuid__in=shot_id_list, is_disabled=False).all()
+
+        file_uuid_id_map = {str(file.uuid): file.id for file in file_list}
+        model_uuid_id_map = {str(model.uuid): model.id for model in model_list}
+        shot_uuid_id_map = {str(shot.uuid): shot.id for shot in shot_list}
+
+        # print("----- file_uuid_map: ", file_uuid_id_map)
+        res_timing_list = []
+        for data in timing_data_list:
+            kwargs = data
+            if 'primary_image_id' in kwargs and kwargs['primary_image_id'] in file_uuid_id_map:
+                kwargs['primary_image_id'] = file_uuid_id_map[kwargs['primary_image_id']]
+
+            if 'source_image_id' in kwargs and kwargs['source_image_id'] in file_uuid_id_map:
+                kwargs['source_image_id'] = file_uuid_id_map[kwargs['source_image_id']]
+
+            if 'mask_id' in kwargs and kwargs['mask_id'] in file_uuid_id_map:
+                kwargs['mask_id'] = file_uuid_id_map[kwargs['mask_id']]
+
+            if 'canny_image_id' in kwargs and kwargs['canny_image_id'] in file_uuid_id_map:
+                kwargs['canny_image_id'] = file_uuid_id_map[kwargs['canny_image_id']]
+
+            if 'shot_id' in kwargs and kwargs['shot_id'] in shot_uuid_id_map:
+                kwargs['shot_id'] = shot_uuid_id_map[kwargs['shot_id']]
+
+            if 'model_id' in kwargs and kwargs['model_id'] in model_uuid_id_map:
+                kwargs['model_id'] = model_uuid_id_map[kwargs['model_id']]
+
+            # print("---- data: ", kwargs)
+            timing = Timing(**kwargs)
+            res_timing_list.append(timing)
+
+        with transaction.atomic():
+            for timing in res_timing_list:
+                timing.save()
+
+        payload = {
+            'data': [TimingDto(timing).data for timing in res_timing_list]
+        }
+        return InternalResponse(payload, 'timing list created successfully', True)
+
     def remove_existing_timing(self, project_uuid):
         if project_uuid:
             project: Project = Project.objects.filter(uuid=project_uuid, is_disabled=False).first()
@@ -944,6 +1018,84 @@ def add_interpolated_clip(self, uuid, **kwargs):
 
         return InternalResponse({}, 'success', True)
 
+    def update_bulk_timing(self, timing_uuid_list, data_list):
+        timing_list = Timing.objects.filter(uuid__in=timing_uuid_list, is_disabled=False).all()
+        if not (timing_list and len(timing_list)) and len(timing_uuid_list):
+            return InternalResponse({}, 'no timing objs found', False)
+
+        primary_image_id_list = []
+        shot_id_list = []
+        model_id_list = []
+        source_image_id_list = []
+        mask_id_list = []
+        canny_image_id_list = []
+
+        for d in data_list:
+            if 'primary_image_id' in d:
+                primary_image_id_list.append(d['primary_image_id'])
+            if 'shot_id' in d:
+                shot_id_list.append(d['shot_id'])
+            if 'model_id' in d:
+                model_id_list.append(d['model_id'])
+            if 'source_image_id' in d:
+                source_image_id_list.append(d['source_image_id'])
+            if 'mask_id' in d:
+                mask_id_list.append(d['mask_id'])
+            if 'canny_image_id' in d:
+                canny_image_id_list.append(d['canny_image_id'])
+            if 'primary_image_id' in d:
+                primary_image_id_list.append(d['primary_image_id'])
+
+        primary_image_id_list = list(set(primary_image_id_list))
+        shot_id_list = list(set(shot_id_list))
+        model_id_list = list(set(model_id_list))
+        source_image_id_list = list(set(source_image_id_list))
+        mask_id_list = list(set(mask_id_list))
+        canny_image_id_list = list(set(canny_image_id_list))
+
+        file_list = InternalFileObject.objects.filter(uuid__in=primary_image_id_list + source_image_id_list + mask_id_list + canny_image_id_list, is_disabled=False).all()
+        model_list = AIModel.objects.filter(uuid__in=model_id_list, is_disabled=False).all()
+        shot_list = Shot.objects.filter(uuid__in=shot_id_list, is_disabled=False).all()
+
+        file_uuid_id_map = {file.uuid: file.id for file in file_list}
+        model_uuid_id_map = {model.uuid: model.id for model in model_list}
+        shot_uuid_id_map = {shot.uuid: shot.id for shot in shot_list}
+
+        res_timing_list = []
+        for timing, update_data in zip(timing_list, data_list):
+            kwargs = update_data
+            if 'primary_image_id' in kwargs and kwargs['primary_image_id'] in file_uuid_id_map:
+                kwargs['primary_image_id'] = file_uuid_id_map[kwargs['primary_image_id']]
+
+            if 'source_image_id' in kwargs and kwargs['source_image_id'] in file_uuid_id_map:
+                kwargs['source_image_id'] = file_uuid_id_map[kwargs['source_image_id']]
+
+            if 'mask_id' in kwargs and kwargs['mask_id'] in file_uuid_id_map:
+                kwargs['mask_id'] = file_uuid_id_map[kwargs['mask_id']]
+
+            if 'canny_image_id' in kwargs and kwargs['canny_image_id'] in file_uuid_id_map:
+                kwargs['canny_image_id'] = file_uuid_id_map[kwargs['canny_image_id']]
+
+            if 'shot_id' in kwargs and kwargs['shot_id'] in shot_uuid_id_map:
+                kwargs['shot_id'] = shot_uuid_id_map[kwargs['shot_id']]
+
+            if 'model_id' in kwargs and kwargs['model_id'] in model_uuid_id_map:
+                kwargs['model_id'] = model_uuid_id_map[kwargs['model_id']]
+
+            for attr, value in kwargs.items():
+                setattr(timing, attr, value)
+
+            res_timing_list.append(timing)
+
+        with transaction.atomic():
+            for timing in res_timing_list:
+                timing.save()
+
+        payload = {
+            'data': [TimingDto(timing).data for timing in res_timing_list]
+        }
+        return InternalResponse(payload, 'timing list updated successfully', True)
+
     def update_specific_timing(self, uuid, **kwargs):
         timing = Timing.objects.filter(uuid=uuid, is_disabled=False).first()
         if not timing:
@@ -999,15 +1151,7 @@ def update_specific_timing(self, uuid, **kwargs):
                     return InternalResponse({}, 'invalid canny image uuid', False)
 
                 kwargs['canny_image_id'] = canny_image.id
-
 
-        if 'primay_image_id' in kwargs:
-            if kwargs['primay_image_id'] != None:
-                primay_image: InternalFileObject = InternalFileObject.objects.filter(uuid=kwargs['primay_image_id'], is_disabled=False).first()
-                if not primay_image:
-                    return InternalResponse({}, 'invalid primary image uuid', False)
-
-                kwargs['primay_image_id'] = primay_image.id
 
         for attr, value in kwargs.items():
             setattr(timing, attr, value)

readme.md

@@ -1,4 +1,4 @@
-# Welcome to Dough v. 0.8.3 (beta)
+# Welcome to Dough v. 0.9.0 (beta)
 
 **⬇️ Scroll down for Setup Instructions - Currently available on Linux & Windows, hosted version coming soon.**
 
@@ -10,28 +10,27 @@ Below is brief overview and some examples of outputs:
 
 ### With Dough, you can makes guidance frames using Stable Diffusion XL, IP-Adapter, Fooocus Inpainting, and more:
 
-<img src="sample_assets/sample_images/generation_example.png" width="800">
+<img src="https://github.com/banodoco/Dough/assets/34690994/698d63f5-765c-4cf2-94f4-7943d241a6ea" width="800">
 
 ### You can then assemble these frames into shots that you can granularly edit:
 
-<img src="sample_assets/sample_images/shot_example.png" width="800">
+<img src="https://github.com/banodoco/Dough/assets/34690994/1080ed90-b829-47cd-b946-de49a7a03b2a" width="800">
 
 ### And then animate these shots by defining parameters for each frame and selecting guidance videos via Motion LoRAs:
 
-<img src="sample_assets/sample_images/motion.png" width="800">
+<img src="https://github.com/banodoco/Dough/assets/34690994/95ec3ec3-5143-40e9-88ba-941ce7e2dec9" width="800">
 
 ### As an example, here's a video that's guided with just images on high strength:
 
-
-<img src="sample_assets/sample_images/just_images.gif" width="800">
+<img src="https://github.com/banodoco/Dough/assets/34690994/cc88ca21-870d-4b96-b9cc-39698fc5fd2f" width="800">
 
 ### While here's a more complex one, with low strength images driving it alongside a guidance video:
 
-<img src="sample_assets/sample_images/cat_walking.gif" width="800">
+<img src="https://github.com/banodoco/Dough/assets/34690994/5c2edc07-8aa3-402f-b119-345db26df8b9" width="800">
 
 ### And here's a more complex example combining high strength guidance with a guidance video strongly influencing the motion:
 
-<img src="sample_assets/sample_images/complex.gif" width="800">
+<img src="https://github.com/banodoco/Dough/assets/34690994/e5d70cc3-03e2-450d-8bc7-b6d1a920af4a" width="800">
 
 
 
@@ -53,28 +52,28 @@ Below is brief overview and some examples of outputs:
 3) During setup, open the relevant ports for Dough like below:
 
 
-<img src="sample_assets/sample_images/runpod_1.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/102bc6fe-0962-493f-b11a-9dfa22501bdd" width="600">
 
-<img src="sample_assets/sample_images/runpod_2.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/1b9ff4d7-960e-496c-83ae-306c0dfa623d" width="600">
 
 
 4) When you’ve launched the pod, click into Jupyter Notebook:
 
-<img src="sample_assets/sample_images/runpod_3.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/9a0b6b54-ae53-4571-8131-165c4bacc909" width="600">
 
-<img src="sample_assets/sample_images/runpod_4.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/86b31523-7457-43b2-ad68-99e62689c32f" width="600">
 
 
 5) Follow the “Setup for Linux” below and come back here when you’ve gone through them.
 
 
 6) Once you’re done that, grab the IP Address for your instance:
 
-<img src="sample_assets/sample_images/runpod_5.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/35aed283-fa47-494e-924e-0263b84be2b2" width="600">
 
-<img src="sample_assets/sample_images/runpod_6.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/2bdb9363-9138-49bd-a2b9-69961e744f7a" width="600">
 
-<img src="sample_assets/sample_images/runpod_7.png" width="600">
+<img src="https://github.com/banodoco/Dough/assets/34690994/a2a83ee6-149e-44aa-b00a-d36e42320bb4" width="600">
 
 Then form put these into this form with a : between them like this:
 
@@ -155,3 +154,51 @@ cd Dough
 ---
 
 If you're having any issues, please share them in our [Discord](https://discord.com/invite/8Wx9dFu5tP).
+
+# Troubleshooting
+
+<details>
+  <summary><b>Common problems (click to expand)</b></summary>
+
+<details>
+  <summary><b>Issue during installation</b></summary>
+
+- Make sure you are using python3.10
+- If you are on Windows, make sure permissions of the Dough folder are not restricted (try to grant full access to everyone)
+- Double-check that you are not inside any system-protected folders like system32
+- Install the app in admin mode. Open the powershell in the admin mode and run "Set-ExecutionPolicy RemoteSigned". Then follow the installation instructions given in the readme
+- If all of the above fail, try to run the following instructions one by one and report which one is throwing the error
+  ```bash
+  call dough-env\Scripts\activate.bat
+  python.exe -m pip install --upgrade pip
+  pip install -r requirements.txt
+  pip install websocket
+  pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+  pip install -r comfy_runner\requirements.txt
+  pip install -r ComfyUI\requirements.txt
+  ```
+</details>
+<details>
+  <summary><b>Unable to locate credentials</b></summary>
+  Make a copy of ".env.sample" and rename it to ".env"
+</details>
+<details>
+  <summary><b>Issue during runtime</b></summary>
+
+- If a particular node inside Comfy is throwing an error then delete that node and restart the app
+- Make sure you are using python3.10 and the virtual environment is activated
+- Try doing "git pull origin main" to get the latest code
+</details>
+<details>
+  <summary><b>Generations are in progress for a long time</b></summary>
+
+- Check the terminal if any progress is being made (they can be very slow, especially in the case of upscaling)
+- Cancel the generations directly from the sidebar if they are stuck
+- If you don't see any logs in the terminal, make sure no other program is running at port 12345 on your machine as Dough uses that port
+</details>
+<details>
+  <summary><b>Some other error?</b></summary>
+  
+  Drop in our [Discord](https://discord.com/invite/8Wx9dFu5tP).
+</details>
+</details>

scripts/app_version.txt

@@ -1 +1 @@
-0.8.3
+0.9.0

ui_components/components/animate_shot_page.py

@@ -1,7 +1,7 @@
 import json
 import time
 import streamlit as st
-from shared.constants import InferenceParamType, InferenceStatus, InferenceType, InternalFileType
+from shared.constants import AnimationStyleType, InferenceParamType, InferenceStatus, InferenceType, InternalFileType
 from ui_components.components.video_rendering_page import sm_video_rendering_page, two_img_realistic_interpolation_page
 from ui_components.models import InternalShotObject
 from ui_components.widgets.frame_selector import frame_selector_widget
@@ -49,6 +49,7 @@ def video_rendering_page(shot_uuid, selected_variant):
             log = data_repo.get_inference_log_from_uuid(selected_variant)
             shot_data = json.loads(log.input_params)
             file_uuid_list = shot_data.get('origin_data', json.dumps({})).get('settings', {}).get('file_uuid_list', [])
+            st.session_state[f"{shot_uuid}_selected_variant_log_uuid"] = None
 
     else:
         # hackish sol, will fix later
@@ -65,6 +66,34 @@ def video_rendering_page(shot_uuid, selected_variant):
         for timing in shot.timing_list:
             if timing.primary_image and timing.primary_image.location:
                 file_uuid_list.append(timing.primary_image.uuid)
+    else:
+        # updating the shot timing images
+        shot_timing_list = shot.timing_list
+        img_mismatch = False    # flag to check if shot images need to be updated
+        if len(file_uuid_list) == len(shot_timing_list):
+            for file_uuid, timing in zip(file_uuid_list, shot_timing_list):
+                if timing.primary_image and timing.primary_image.uuid != file_uuid:
+                    img_mismatch = True
+                    break
+        else:
+            img_mismatch = True
+
+        if img_mismatch or len(file_uuid_list) != len(shot_timing_list):
+            # deleting all the current timings
+            data_repo.update_bulk_timing([timing.uuid for timing in shot_timing_list], [{'is_disabled': True}] * len(shot_timing_list))
+            # adding new timings
+            new_timing_data = []
+            for idx, file_uuid in enumerate(file_uuid_list):
+                new_timing_data.append(
+                    {
+                        'aux_frame_index': idx, 
+                        'shot_id': shot_uuid, 
+                        'primary_image_id': file_uuid,
+                        'is_disabled': False
+                    }
+                )
+
+            data_repo.bulk_create_timing(new_timing_data)
 
     img_list = data_repo.get_all_file_list(uuid__in=file_uuid_list, file_type=InternalFileType.IMAGE.value)[0]    
 

ui_components/components/explorer_page.py

@@ -491,7 +491,7 @@ def gallery_image_view(project_uuid, shortlist=False, view=["main"], shot=None,
         else:
             with h1:
                 project_setting = data_repo.get_project_setting(project_uuid)
-                page_number = k1.radio("Select page", options=range(1, project_setting.total_shortlist_gallery_pages), horizontal=True, key="shortlist_gallery")
+                page_number = k1.radio("Select page", options=range(1, project_setting.total_shortlist_gallery_pages + 1), horizontal=True, key="shortlist_gallery")
                 open_detailed_view_for_all = False     
 
     else:
@@ -620,7 +620,9 @@ def gallery_image_view(project_uuid, shortlist=False, view=["main"], shot=None,
                             log = gallery_image_list[i + j].inference_log # data_repo.get_inference_log_from_uuid(gallery_image_list[i + j].inference_log.uuid)
                             if log:
                                 input_params = json.loads(log.input_params)
-                                prompt = input_params.get('prompt', 'No prompt found')
+                                prompt = input_params.get('prompt', None)
+                                if not prompt:
+                                    prompt = input_params.get("query_dict", {}).get("prompt", "Prompt not found")
                                 model = json.loads(log.output_details)['model_name'].split('/')[-1]
                                 if 'view_inference_details' in view:
                                     with st.expander("Prompt Details", expanded=open_detailed_view_for_all):